Computational_drug_discovery_project.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "iWjEpfrs3hm-",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "adc8cc10-addb-4583-bd7d-d48d711ac97b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting chembl_webresource_client\n",
            "  Downloading chembl_webresource_client-0.10.8-py3-none-any.whl (55 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/55.2 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[91m╸\u001b[0m\u001b[90m━━━━━━━━━━\u001b[0m \u001b[32m41.0/55.2 kB\u001b[0m \u001b[31m1.1 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m55.2/55.2 kB\u001b[0m \u001b[31m879.2 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: urllib3 in /usr/local/lib/python3.10/dist-packages (from chembl_webresource_client) (2.0.7)\n",
            "Requirement already satisfied: requests>=2.18.4 in /usr/local/lib/python3.10/dist-packages (from chembl_webresource_client) (2.31.0)\n",
            "Collecting requests-cache~=0.7.0 (from chembl_webresource_client)\n",
            "  Downloading requests_cache-0.7.5-py3-none-any.whl (39 kB)\n",
            "Requirement already satisfied: easydict in /usr/local/lib/python3.10/dist-packages (from chembl_webresource_client) (1.11)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.18.4->chembl_webresource_client) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.18.4->chembl_webresource_client) (3.6)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.18.4->chembl_webresource_client) (2023.11.17)\n",
            "Collecting attrs<22.0,>=21.2 (from requests-cache~=0.7.0->chembl_webresource_client)\n",
            "  Downloading attrs-21.4.0-py2.py3-none-any.whl (60 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m60.6/60.6 kB\u001b[0m \u001b[31m4.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: itsdangerous>=2.0.1 in /usr/local/lib/python3.10/dist-packages (from requests-cache~=0.7.0->chembl_webresource_client) (2.1.2)\n",
            "Requirement already satisfied: pyyaml>=5.4 in /usr/local/lib/python3.10/dist-packages (from requests-cache~=0.7.0->chembl_webresource_client) (6.0.1)\n",
            "Collecting url-normalize<2.0,>=1.4 (from requests-cache~=0.7.0->chembl_webresource_client)\n",
            "  Downloading url_normalize-1.4.3-py2.py3-none-any.whl (6.8 kB)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from url-normalize<2.0,>=1.4->requests-cache~=0.7.0->chembl_webresource_client) (1.16.0)\n",
            "Installing collected packages: url-normalize, attrs, requests-cache, chembl_webresource_client\n",
            "  Attempting uninstall: attrs\n",
            "    Found existing installation: attrs 23.1.0\n",
            "    Uninstalling attrs-23.1.0:\n",
            "      Successfully uninstalled attrs-23.1.0\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "lida 0.0.10 requires fastapi, which is not installed.\n",
            "lida 0.0.10 requires kaleido, which is not installed.\n",
            "lida 0.0.10 requires python-multipart, which is not installed.\n",
            "lida 0.0.10 requires uvicorn, which is not installed.\n",
            "jsonschema 4.19.2 requires attrs>=22.2.0, but you have attrs 21.4.0 which is incompatible.\n",
            "referencing 0.32.0 requires attrs>=22.2.0, but you have attrs 21.4.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed attrs-21.4.0 chembl_webresource_client-0.10.8 requests-cache-0.7.5 url-normalize-1.4.3\n"
          ]
        }
      ],
      "source": [
        "! pip install chembl_webresource_client"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "from chembl_webresource_client.new_client import new_client"
      ],
      "metadata": {
        "id": "UY4HuDwB6V-v"
      },
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1FgUai1bfigC"
      },
      "source": [
        "## **Search for Target protein**"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "target = new_client.target\n",
        "target_query = target.search('coronavirus')\n",
        "targets = pd.DataFrame.from_dict(target_query)\n",
        "targets"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 432
        },
        "id": "y42Ce8hj7WCf",
        "outputId": "aadc7d40-2a47-4660-b2b9-cec860fe2b55"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                    cross_references  \\\n",
              "0                                                 []   \n",
              "1                                                 []   \n",
              "2                                                 []   \n",
              "3                                                 []   \n",
              "4                                                 []   \n",
              "5                                                 []   \n",
              "6  [{'xref_id': 'P0C6U8', 'xref_name': None, 'xre...   \n",
              "7                                                 []   \n",
              "8  [{'xref_id': 'P0C6X7', 'xref_name': None, 'xre...   \n",
              "9                                                 []   \n",
              "\n",
              "                                            organism  \\\n",
              "0                                        Coronavirus   \n",
              "1                                   SARS coronavirus   \n",
              "2                                 Feline coronavirus   \n",
              "3                                 Murine coronavirus   \n",
              "4                             Human coronavirus 229E   \n",
              "5                             Human coronavirus OC43   \n",
              "6                                   SARS coronavirus   \n",
              "7  Middle East respiratory syndrome-related coron...   \n",
              "8                                   SARS coronavirus   \n",
              "9    Severe acute respiratory syndrome coronavirus 2   \n",
              "\n",
              "                                           pref_name  score  \\\n",
              "0                                        Coronavirus   17.0   \n",
              "1                                   SARS coronavirus   14.0   \n",
              "2                                 Feline coronavirus   14.0   \n",
              "3                                 Murine coronavirus   14.0   \n",
              "4                             Human coronavirus 229E   12.0   \n",
              "5                             Human coronavirus OC43   12.0   \n",
              "6                SARS coronavirus 3C-like proteinase   10.0   \n",
              "7  Middle East respiratory syndrome-related coron...    9.0   \n",
              "8                          Replicase polyprotein 1ab    4.0   \n",
              "9                          Replicase polyprotein 1ab    4.0   \n",
              "\n",
              "   species_group_flag target_chembl_id  \\\n",
              "0               False     CHEMBL613732   \n",
              "1               False     CHEMBL612575   \n",
              "2               False     CHEMBL612744   \n",
              "3               False    CHEMBL5209664   \n",
              "4               False     CHEMBL613837   \n",
              "5               False    CHEMBL5209665   \n",
              "6               False       CHEMBL3927   \n",
              "7               False    CHEMBL4296578   \n",
              "8               False       CHEMBL5118   \n",
              "9               False    CHEMBL4523582   \n",
              "\n",
              "                                   target_components     target_type   tax_id  \n",
              "0                                                 []        ORGANISM    11119  \n",
              "1                                                 []        ORGANISM   227859  \n",
              "2                                                 []        ORGANISM    12663  \n",
              "3                                                 []        ORGANISM   694005  \n",
              "4                                                 []        ORGANISM    11137  \n",
              "5                                                 []        ORGANISM    31631  \n",
              "6  [{'accession': 'P0C6U8', 'component_descriptio...  SINGLE PROTEIN   227859  \n",
              "7                                                 []        ORGANISM  1335626  \n",
              "8  [{'accession': 'P0C6X7', 'component_descriptio...  SINGLE PROTEIN   227859  \n",
              "9  [{'accession': 'P0DTD1', 'component_descriptio...  SINGLE PROTEIN  2697049  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-572bf19e-75df-48a9-974e-0405fc4bb61c\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>cross_references</th>\n",
              "      <th>organism</th>\n",
              "      <th>pref_name</th>\n",
              "      <th>score</th>\n",
              "      <th>species_group_flag</th>\n",
              "      <th>target_chembl_id</th>\n",
              "      <th>target_components</th>\n",
              "      <th>target_type</th>\n",
              "      <th>tax_id</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>[]</td>\n",
              "      <td>Coronavirus</td>\n",
              "      <td>Coronavirus</td>\n",
              "      <td>17.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL613732</td>\n",
              "      <td>[]</td>\n",
              "      <td>ORGANISM</td>\n",
              "      <td>11119</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>[]</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>14.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL612575</td>\n",
              "      <td>[]</td>\n",
              "      <td>ORGANISM</td>\n",
              "      <td>227859</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>[]</td>\n",
              "      <td>Feline coronavirus</td>\n",
              "      <td>Feline coronavirus</td>\n",
              "      <td>14.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL612744</td>\n",
              "      <td>[]</td>\n",
              "      <td>ORGANISM</td>\n",
              "      <td>12663</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>[]</td>\n",
              "      <td>Murine coronavirus</td>\n",
              "      <td>Murine coronavirus</td>\n",
              "      <td>14.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL5209664</td>\n",
              "      <td>[]</td>\n",
              "      <td>ORGANISM</td>\n",
              "      <td>694005</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>[]</td>\n",
              "      <td>Human coronavirus 229E</td>\n",
              "      <td>Human coronavirus 229E</td>\n",
              "      <td>12.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL613837</td>\n",
              "      <td>[]</td>\n",
              "      <td>ORGANISM</td>\n",
              "      <td>11137</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>[]</td>\n",
              "      <td>Human coronavirus OC43</td>\n",
              "      <td>Human coronavirus OC43</td>\n",
              "      <td>12.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL5209665</td>\n",
              "      <td>[]</td>\n",
              "      <td>ORGANISM</td>\n",
              "      <td>31631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>[{'xref_id': 'P0C6U8', 'xref_name': None, 'xre...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>SARS coronavirus 3C-like proteinase</td>\n",
              "      <td>10.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL3927</td>\n",
              "      <td>[{'accession': 'P0C6U8', 'component_descriptio...</td>\n",
              "      <td>SINGLE PROTEIN</td>\n",
              "      <td>227859</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>[]</td>\n",
              "      <td>Middle East respiratory syndrome-related coron...</td>\n",
              "      <td>Middle East respiratory syndrome-related coron...</td>\n",
              "      <td>9.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL4296578</td>\n",
              "      <td>[]</td>\n",
              "      <td>ORGANISM</td>\n",
              "      <td>1335626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>[{'xref_id': 'P0C6X7', 'xref_name': None, 'xre...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>4.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL5118</td>\n",
              "      <td>[{'accession': 'P0C6X7', 'component_descriptio...</td>\n",
              "      <td>SINGLE PROTEIN</td>\n",
              "      <td>227859</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>[]</td>\n",
              "      <td>Severe acute respiratory syndrome coronavirus 2</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>4.0</td>\n",
              "      <td>False</td>\n",
              "      <td>CHEMBL4523582</td>\n",
              "      <td>[{'accession': 'P0DTD1', 'component_descriptio...</td>\n",
              "      <td>SINGLE PROTEIN</td>\n",
              "      <td>2697049</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-572bf19e-75df-48a9-974e-0405fc4bb61c')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-572bf19e-75df-48a9-974e-0405fc4bb61c button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-572bf19e-75df-48a9-974e-0405fc4bb61c');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-03700a35-6f2d-4f5d-9951-73a9d605d39a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-03700a35-6f2d-4f5d-9951-73a9d605d39a')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-03700a35-6f2d-4f5d-9951-73a9d605d39a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_03bd16b5-f908-42e4-9e6f-b1129ad79921\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('targets')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_03bd16b5-f908-42e4-9e6f-b1129ad79921 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('targets');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "selected_target = targets.target_chembl_id[8]\n",
        "selected_target"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "NjsBjLLn_FlI",
        "outputId": "a2ea13a1-de23-4eb5-c3ff-6532598d972e"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'CHEMBL5118'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Replicase polyprotein 1ab (Severe acute respiratory syndrome-related coronavirus)**\n",
        "Multifunctional protein involved in the transcription and replication of viral RNAs. Contains the proteinases responsible for the cleavages of the polyprotein.\n",
        "\n",
        "Inhibits host translation by interacting with the 40S ribosomal subunit. The nsp1-40S ribosome complex further induces an endonucleolytic cleavage near the 5'UTR of host mRNAs, targeting them for degradation. Viral mRNAs are not susceptible to nsp1-mediated endonucleolytic RNA cleavage thanks to the presence of a 5'-end leader sequence and are therefore protected from degradation. By suppressing host gene expression, nsp1 facilitates efficient viral gene expression in infected cells and evasion from host immune response (PMID: 23035226)."
      ],
      "metadata": {
        "id": "hQMN2YUlZUiE"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GWd2DRalgjzB"
      },
      "source": [
        "Here, we will retrieve only bioactivity data for *Replicase polyprotein 1ab * (CHEMBL5118) that are reported as IC$_{50}$ values in nM (nanomolar) unit."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "activity= new_client.activity\n",
        "res = activity.filter(target_chembl_id=selected_target).filter(standard_type=\"IC50\")"
      ],
      "metadata": {
        "id": "isC6ICHXCDNU"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame.from_dict(res)"
      ],
      "metadata": {
        "id": "Kmja6Dj8CDRr"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 231
        },
        "id": "K5OrxaIMft3j",
        "outputId": "e473228c-fdd2-47c8-945e-1fa338bc9463"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  action_type activity_comment  activity_id activity_properties  \\\n",
              "0        None             None      1988091                  []   \n",
              "1        None             None      1988092                  []   \n",
              "\n",
              "  assay_chembl_id                                  assay_description  \\\n",
              "0    CHEMBL898907  Inhibition of SARS-CoV 3C-like protease by FRE...   \n",
              "1    CHEMBL898907  Inhibition of SARS-CoV 3C-like protease by FRE...   \n",
              "\n",
              "  assay_type assay_variant_accession assay_variant_mutation bao_endpoint  ...  \\\n",
              "0          B                    None                   None  BAO_0000190  ...   \n",
              "1          B                    None                   None  BAO_0000190  ...   \n",
              "\n",
              "    target_organism           target_pref_name target_tax_id text_value  toid  \\\n",
              "0  SARS coronavirus  Replicase polyprotein 1ab        227859       None  None   \n",
              "1  SARS coronavirus  Replicase polyprotein 1ab        227859       None  None   \n",
              "\n",
              "   type units    uo_units upper_value  value  \n",
              "0  IC50    uM  UO_0000065        None  870.0  \n",
              "1  IC50    uM  UO_0000065        None  200.0  \n",
              "\n",
              "[2 rows x 46 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0a07b5ac-dac6-4108-b482-a6ea5fb0cf84\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>action_type</th>\n",
              "      <th>activity_comment</th>\n",
              "      <th>activity_id</th>\n",
              "      <th>activity_properties</th>\n",
              "      <th>assay_chembl_id</th>\n",
              "      <th>assay_description</th>\n",
              "      <th>assay_type</th>\n",
              "      <th>assay_variant_accession</th>\n",
              "      <th>assay_variant_mutation</th>\n",
              "      <th>bao_endpoint</th>\n",
              "      <th>...</th>\n",
              "      <th>target_organism</th>\n",
              "      <th>target_pref_name</th>\n",
              "      <th>target_tax_id</th>\n",
              "      <th>text_value</th>\n",
              "      <th>toid</th>\n",
              "      <th>type</th>\n",
              "      <th>units</th>\n",
              "      <th>uo_units</th>\n",
              "      <th>upper_value</th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1988091</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL898907</td>\n",
              "      <td>Inhibition of SARS-CoV 3C-like protease by FRE...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>870.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1988092</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL898907</td>\n",
              "      <td>Inhibition of SARS-CoV 3C-like protease by FRE...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>200.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2 rows × 46 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0a07b5ac-dac6-4108-b482-a6ea5fb0cf84')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-0a07b5ac-dac6-4108-b482-a6ea5fb0cf84 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-0a07b5ac-dac6-4108-b482-a6ea5fb0cf84');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-68bf66b7-23ad-457a-8934-beae36cf8c14\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-68bf66b7-23ad-457a-8934-beae36cf8c14')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-68bf66b7-23ad-457a-8934-beae36cf8c14 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv('bioactivity_data_raw.csv',index=False)"
      ],
      "metadata": {
        "id": "YI24edV_MCfW"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df2 = df[df.standard_value.notna()]\n",
        "df2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 791
        },
        "id": "fAwa-b9UNwC6",
        "outputId": "65b3f5fb-7166-4896-94fd-4810beb7686d"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    action_type activity_comment  activity_id activity_properties  \\\n",
              "0          None             None      1988091                  []   \n",
              "1          None             None      1988092                  []   \n",
              "2          None             None      1988093                  []   \n",
              "3          None             None      1988094                  []   \n",
              "4          None             None      1988095                  []   \n",
              "..          ...              ...          ...                 ...   \n",
              "210        None             None     18548176                  []   \n",
              "211        None             None     18548177                  []   \n",
              "212        None             None     18548178                  []   \n",
              "213        None             None     18548179                  []   \n",
              "214        None             None     18548180                  []   \n",
              "\n",
              "    assay_chembl_id                                  assay_description  \\\n",
              "0      CHEMBL898907  Inhibition of SARS-CoV 3C-like protease by FRE...   \n",
              "1      CHEMBL898907  Inhibition of SARS-CoV 3C-like protease by FRE...   \n",
              "2      CHEMBL898907  Inhibition of SARS-CoV 3C-like protease by FRE...   \n",
              "3      CHEMBL898907  Inhibition of SARS-CoV 3C-like protease by FRE...   \n",
              "4      CHEMBL898907  Inhibition of SARS-CoV 3C-like protease by FRE...   \n",
              "..              ...                                                ...   \n",
              "210   CHEMBL4198706  Inhibition of SARS coronavirus 3CL protease us...   \n",
              "211   CHEMBL4198706  Inhibition of SARS coronavirus 3CL protease us...   \n",
              "212   CHEMBL4198706  Inhibition of SARS coronavirus 3CL protease us...   \n",
              "213   CHEMBL4198706  Inhibition of SARS coronavirus 3CL protease us...   \n",
              "214   CHEMBL4198706  Inhibition of SARS coronavirus 3CL protease us...   \n",
              "\n",
              "    assay_type assay_variant_accession assay_variant_mutation bao_endpoint  \\\n",
              "0            B                    None                   None  BAO_0000190   \n",
              "1            B                    None                   None  BAO_0000190   \n",
              "2            B                    None                   None  BAO_0000190   \n",
              "3            B                    None                   None  BAO_0000190   \n",
              "4            B                    None                   None  BAO_0000190   \n",
              "..         ...                     ...                    ...          ...   \n",
              "210          B                    None                   None  BAO_0000190   \n",
              "211          B                    None                   None  BAO_0000190   \n",
              "212          B                    None                   None  BAO_0000190   \n",
              "213          B                    None                   None  BAO_0000190   \n",
              "214          B                    None                   None  BAO_0000190   \n",
              "\n",
              "     ...   target_organism           target_pref_name target_tax_id  \\\n",
              "0    ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "1    ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "2    ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "3    ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "4    ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "..   ...               ...                        ...           ...   \n",
              "210  ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "211  ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "212  ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "213  ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "214  ...  SARS coronavirus  Replicase polyprotein 1ab        227859   \n",
              "\n",
              "    text_value  toid  type units    uo_units upper_value  value  \n",
              "0         None  None  IC50    uM  UO_0000065        None  870.0  \n",
              "1         None  None  IC50    uM  UO_0000065        None  200.0  \n",
              "2         None  None  IC50    uM  UO_0000065        None  300.0  \n",
              "3         None  None  IC50    uM  UO_0000065        None   15.0  \n",
              "4         None  None  IC50    uM  UO_0000065        None   10.0  \n",
              "..         ...   ...   ...   ...         ...         ...    ...  \n",
              "210       None  None  IC50    uM  UO_0000065        None    4.3  \n",
              "211       None  None  IC50    uM  UO_0000065        None    5.5  \n",
              "212       None  None  IC50    uM  UO_0000065        None    4.1  \n",
              "213       None  None  IC50    uM  UO_0000065        None    3.2  \n",
              "214       None  None  IC50    uM  UO_0000065        None    8.8  \n",
              "\n",
              "[214 rows x 46 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-82342ac1-2f87-487c-a1a9-6b1faf4cc054\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>action_type</th>\n",
              "      <th>activity_comment</th>\n",
              "      <th>activity_id</th>\n",
              "      <th>activity_properties</th>\n",
              "      <th>assay_chembl_id</th>\n",
              "      <th>assay_description</th>\n",
              "      <th>assay_type</th>\n",
              "      <th>assay_variant_accession</th>\n",
              "      <th>assay_variant_mutation</th>\n",
              "      <th>bao_endpoint</th>\n",
              "      <th>...</th>\n",
              "      <th>target_organism</th>\n",
              "      <th>target_pref_name</th>\n",
              "      <th>target_tax_id</th>\n",
              "      <th>text_value</th>\n",
              "      <th>toid</th>\n",
              "      <th>type</th>\n",
              "      <th>units</th>\n",
              "      <th>uo_units</th>\n",
              "      <th>upper_value</th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1988091</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL898907</td>\n",
              "      <td>Inhibition of SARS-CoV 3C-like protease by FRE...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>870.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1988092</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL898907</td>\n",
              "      <td>Inhibition of SARS-CoV 3C-like protease by FRE...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>200.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1988093</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL898907</td>\n",
              "      <td>Inhibition of SARS-CoV 3C-like protease by FRE...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>300.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1988094</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL898907</td>\n",
              "      <td>Inhibition of SARS-CoV 3C-like protease by FRE...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1988095</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL898907</td>\n",
              "      <td>Inhibition of SARS-CoV 3C-like protease by FRE...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>18548176</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL4198706</td>\n",
              "      <td>Inhibition of SARS coronavirus 3CL protease us...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>4.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>18548177</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL4198706</td>\n",
              "      <td>Inhibition of SARS coronavirus 3CL protease us...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>5.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>18548178</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL4198706</td>\n",
              "      <td>Inhibition of SARS coronavirus 3CL protease us...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>4.1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>18548179</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL4198706</td>\n",
              "      <td>Inhibition of SARS coronavirus 3CL protease us...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>3.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214</th>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>18548180</td>\n",
              "      <td>[]</td>\n",
              "      <td>CHEMBL4198706</td>\n",
              "      <td>Inhibition of SARS coronavirus 3CL protease us...</td>\n",
              "      <td>B</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>BAO_0000190</td>\n",
              "      <td>...</td>\n",
              "      <td>SARS coronavirus</td>\n",
              "      <td>Replicase polyprotein 1ab</td>\n",
              "      <td>227859</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>IC50</td>\n",
              "      <td>uM</td>\n",
              "      <td>UO_0000065</td>\n",
              "      <td>None</td>\n",
              "      <td>8.8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>214 rows × 46 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-82342ac1-2f87-487c-a1a9-6b1faf4cc054')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-82342ac1-2f87-487c-a1a9-6b1faf4cc054 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-82342ac1-2f87-487c-a1a9-6b1faf4cc054');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-398a1a7b-bcfb-486b-9755-ffa1ca40e204\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-398a1a7b-bcfb-486b-9755-ffa1ca40e204')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-398a1a7b-bcfb-486b-9755-ffa1ca40e204 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_106156df-dcad-4139-8e62-f3cbd7dbe7c5\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df2')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_106156df-dcad-4139-8e62-f3cbd7dbe7c5 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df2');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5H4sSFAWhV9B"
      },
      "source": [
        "## **Data pre-processing of the bioactivity data**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tO22XVlzhkXR"
      },
      "source": [
        "### **Labeling compounds as either being active, inactive or intermediate**\n",
        "The bioactivity data is in the IC50 unit. Compounds having values of less than 1000 nM will be considered to be **active** while those greater than 10,000 nM will be considered to be **inactive**. As for those values in between 1,000 and 10,000 nM will be referred to as **intermediate**."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bioactivity_class= []\n",
        "for i in df2.standard_value:\n",
        "  if float(i) >= 10000:\n",
        "    bioactivity_class.append(\"inactive\")\n",
        "  elif float(i) <= 1000:\n",
        "    bioactivity_class.append(\"active\")\n",
        "  else:\n",
        "    bioactivity_class.append(\"intermediate\")"
      ],
      "metadata": {
        "id": "WqYMyMekNv96"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nv2dzid_hzKd"
      },
      "source": [
        "### **Combine the 3 columns (molecule_chembl_id,canonical_smiles,standard_value) and bioactivity_class into a DataFrame**"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df2.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FPSHMbVinSCg",
        "outputId": "9eb4b1ab-d863-46c8-ba9f-5f861da49abb"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['action_type', 'activity_comment', 'activity_id', 'activity_properties',\n",
              "       'assay_chembl_id', 'assay_description', 'assay_type',\n",
              "       'assay_variant_accession', 'assay_variant_mutation', 'bao_endpoint',\n",
              "       'bao_format', 'bao_label', 'canonical_smiles', 'data_validity_comment',\n",
              "       'data_validity_description', 'document_chembl_id', 'document_journal',\n",
              "       'document_year', 'ligand_efficiency', 'molecule_chembl_id',\n",
              "       'molecule_pref_name', 'parent_molecule_chembl_id', 'pchembl_value',\n",
              "       'potential_duplicate', 'qudt_units', 'record_id', 'relation', 'src_id',\n",
              "       'standard_flag', 'standard_relation', 'standard_text_value',\n",
              "       'standard_type', 'standard_units', 'standard_upper_value',\n",
              "       'standard_value', 'target_chembl_id', 'target_organism',\n",
              "       'target_pref_name', 'target_tax_id', 'text_value', 'toid', 'type',\n",
              "       'units', 'uo_units', 'upper_value', 'value'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "selection = ['molecule_chembl_id','canonical_smiles','standard_value']\n",
        "df3 = df2[selection]"
      ],
      "metadata": {
        "id": "5qCLR4cDnOm1"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "gH9cXXh1pTjJ",
        "outputId": "dfa0ff45-f780-4f0c-abab-daac0c65ce38"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    molecule_chembl_id                                   canonical_smiles  \\\n",
              "0         CHEMBL194398  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...   \n",
              "1         CHEMBL393608  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "2         CHEMBL238216  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "3         CHEMBL235873  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "4         CHEMBL397154  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "..                 ...                                                ...   \n",
              "210      CHEMBL4208764  CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...   \n",
              "211      CHEMBL4212620  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...   \n",
              "212      CHEMBL4216101  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...   \n",
              "213      CHEMBL4217568  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...   \n",
              "214      CHEMBL4204431  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...   \n",
              "\n",
              "    standard_value  \n",
              "0         870000.0  \n",
              "1         200000.0  \n",
              "2         300000.0  \n",
              "3          15000.0  \n",
              "4          10000.0  \n",
              "..             ...  \n",
              "210         4300.0  \n",
              "211         5500.0  \n",
              "212         4100.0  \n",
              "213         3200.0  \n",
              "214         8800.0  \n",
              "\n",
              "[214 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-99d75339-cce4-4f6d-ab9f-833f72dc9c71\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>canonical_smiles</th>\n",
              "      <th>standard_value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL194398</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...</td>\n",
              "      <td>870000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL393608</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>200000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL238216</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>300000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL235873</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>15000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL397154</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>10000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>CHEMBL4208764</td>\n",
              "      <td>CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...</td>\n",
              "      <td>4300.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>CHEMBL4212620</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...</td>\n",
              "      <td>5500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>CHEMBL4216101</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...</td>\n",
              "      <td>4100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>CHEMBL4217568</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...</td>\n",
              "      <td>3200.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214</th>\n",
              "      <td>CHEMBL4204431</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...</td>\n",
              "      <td>8800.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>214 rows × 3 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-99d75339-cce4-4f6d-ab9f-833f72dc9c71')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-99d75339-cce4-4f6d-ab9f-833f72dc9c71 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-99d75339-cce4-4f6d-ab9f-833f72dc9c71');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-fc5bad03-6bd7-47a0-9266-c03b080155bf\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fc5bad03-6bd7-47a0-9266-c03b080155bf')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-fc5bad03-6bd7-47a0-9266-c03b080155bf button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_bc53f783-d4d4-4bc3-9a7a-9df8a680e047\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df3')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_bc53f783-d4d4-4bc3-9a7a-9df8a680e047 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df3');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bioactivity_class = pd.Series(bioactivity_class, name='bioactivity_class')\n",
        "df4 = pd.concat([df3,bioactivity_class], axis=1)"
      ],
      "metadata": {
        "id": "Lhr8jXG5MTtc"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df4 = df4[df.standard_value.notna()]\n",
        "df4"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "VwA91TXfqLAc",
        "outputId": "1bd92b6b-2874-4ebe-b4d0-7f5b15eb0a9e"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-15-f7d51f1ce9ac>:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
            "  df4 = df4[df.standard_value.notna()]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    molecule_chembl_id                                   canonical_smiles  \\\n",
              "0         CHEMBL194398  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...   \n",
              "1         CHEMBL393608  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "2         CHEMBL238216  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "3         CHEMBL235873  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "4         CHEMBL397154  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "..                 ...                                                ...   \n",
              "210      CHEMBL4208764  CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...   \n",
              "211      CHEMBL4212620  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...   \n",
              "212      CHEMBL4216101  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...   \n",
              "213      CHEMBL4217568  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...   \n",
              "214      CHEMBL4204431  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...   \n",
              "\n",
              "    standard_value bioactivity_class  \n",
              "0         870000.0          inactive  \n",
              "1         200000.0          inactive  \n",
              "2         300000.0          inactive  \n",
              "3          15000.0          inactive  \n",
              "4          10000.0          inactive  \n",
              "..             ...               ...  \n",
              "210         4300.0      intermediate  \n",
              "211         5500.0      intermediate  \n",
              "212         4100.0      intermediate  \n",
              "213         3200.0      intermediate  \n",
              "214         8800.0               NaN  \n",
              "\n",
              "[214 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c716cb5b-7eb1-4cf4-8f23-902d8dfa2208\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>canonical_smiles</th>\n",
              "      <th>standard_value</th>\n",
              "      <th>bioactivity_class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL194398</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...</td>\n",
              "      <td>870000.0</td>\n",
              "      <td>inactive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL393608</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>200000.0</td>\n",
              "      <td>inactive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL238216</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>300000.0</td>\n",
              "      <td>inactive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL235873</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>15000.0</td>\n",
              "      <td>inactive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL397154</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>10000.0</td>\n",
              "      <td>inactive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>CHEMBL4208764</td>\n",
              "      <td>CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...</td>\n",
              "      <td>4300.0</td>\n",
              "      <td>intermediate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>CHEMBL4212620</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...</td>\n",
              "      <td>5500.0</td>\n",
              "      <td>intermediate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>CHEMBL4216101</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...</td>\n",
              "      <td>4100.0</td>\n",
              "      <td>intermediate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>CHEMBL4217568</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...</td>\n",
              "      <td>3200.0</td>\n",
              "      <td>intermediate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214</th>\n",
              "      <td>CHEMBL4204431</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...</td>\n",
              "      <td>8800.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>214 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c716cb5b-7eb1-4cf4-8f23-902d8dfa2208')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-c716cb5b-7eb1-4cf4-8f23-902d8dfa2208 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c716cb5b-7eb1-4cf4-8f23-902d8dfa2208');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-211b52c3-48f1-4187-ac45-84c675c489ec\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-211b52c3-48f1-4187-ac45-84c675c489ec')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-211b52c3-48f1-4187-ac45-84c675c489ec button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_be6385e2-40a1-40f6-9075-06d28f44b36e\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df4')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_be6385e2-40a1-40f6-9075-06d28f44b36e button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df4');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df4.to_csv('bioactivity_data_preprocessed.csv',index=False)\n",
        "! ls -l"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DICLfCYJOVXn",
        "outputId": "d2b959d5-194d-46cd-887c-3d8c733d9d2b"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 144\n",
            "-rw-r--r-- 1 root root  19302 Jan  6 12:21 bioactivity_data_preprocessed.csv\n",
            "-rw-r--r-- 1 root root 119301 Jan  6 12:21 bioactivity_data_raw.csv\n",
            "drwxr-xr-x 1 root root   4096 Jan  4 14:21 sample_data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#copying it to google drive\n",
        "! cp bioactivity_data_preprocessed.csv \"/content/gdrive/My Drive/Colab Notebooks/Computational drug discovery\"\n",
        "! ls \"/content/gdrive/My Drive/Colab Notebooks/Computational drug discovery\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zQRkkhj8OnkZ",
        "outputId": "80ef2120-bb68-415d-df6d-9f4932070c8a"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "cp: cannot create regular file '/content/gdrive/My Drive/Colab Notebooks/Computational drug discovery': No such file or directory\n",
            "ls: cannot access '/content/gdrive/My Drive/Colab Notebooks/Computational drug discovery': No such file or directory\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **PART 2**"
      ],
      "metadata": {
        "id": "9BfiMBzL6AN_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "! wget https://repo.anaconda.com/miniconda/Miniconda3-py37_4.8.2-Linux-x86_64.sh\n",
        "! chmod +x Miniconda3-py37_4.8.2-Linux-x86_64.sh\n",
        "! bash ./Miniconda3-py37_4.8.2-Linux-x86_64.sh -b -f -p /usr/local\n",
        "! conda install -c rdkit rdkit -y\n",
        "import sys\n",
        "sys.path.append('/usr/local/lib/python3.7/site-packages/')"
      ],
      "metadata": {
        "id": "W9FJnxJi-ePZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "df = pd.read_csv('bioactivity_data_preprocessed.csv')"
      ],
      "metadata": {
        "id": "m__VjS07Gqms"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "!pip install rdkit"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YXXp_FsQLSz6",
        "outputId": "d6699802-1f98-4f8c-d697-8b6134f39775"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting rdkit\n",
            "  Downloading rdkit-2023.3.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (29.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 29.5 MB 1.5 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.7/site-packages (from rdkit) (1.21.5)\n",
            "Requirement already satisfied: Pillow in /usr/local/lib/python3.7/site-packages (from rdkit) (8.3.1)\n",
            "Installing collected packages: rdkit\n",
            "Successfully installed rdkit-2023.3.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from rdkit import Chem\n",
        "from rdkit.Chem import Descriptors, Lipinski"
      ],
      "metadata": {
        "id": "zgBjqknNL-jG"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bCXEY7a9ugO_"
      },
      "source": [
        "# Inspired by: https://codeocean.com/explore/capsules?query=tag:data-curation\n",
        "\n",
        "def lipinski(smiles, verbose=False):\n",
        "\n",
        "    moldata= []\n",
        "    for elem in smiles:\n",
        "        mol=Chem.MolFromSmiles(elem)\n",
        "        moldata.append(mol)\n",
        "\n",
        "    baseData= np.arange(1,1)\n",
        "    i=0\n",
        "    for mol in moldata:\n",
        "\n",
        "        desc_MolWt = Descriptors.MolWt(mol)\n",
        "        desc_MolLogP = Descriptors.MolLogP(mol)\n",
        "        desc_NumHDonors = Lipinski.NumHDonors(mol)\n",
        "        desc_NumHAcceptors = Lipinski.NumHAcceptors(mol)\n",
        "\n",
        "        row = np.array([desc_MolWt,\n",
        "                        desc_MolLogP,\n",
        "                        desc_NumHDonors,\n",
        "                        desc_NumHAcceptors])\n",
        "\n",
        "        if(i==0):\n",
        "            baseData=row\n",
        "        else:\n",
        "            baseData=np.vstack([baseData, row])\n",
        "        i=i+1\n",
        "\n",
        "    columnNames=[\"MW\",\"LogP\",\"NumHDonors\",\"NumHAcceptors\"]\n",
        "    descriptors = pd.DataFrame(data=baseData,columns=columnNames)\n",
        "\n",
        "    return descriptors"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_lipinski= lipinski(df.canonical_smiles)\n",
        "df_lipinski"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "bbpTffV-DpTO",
        "outputId": "5f32d3bb-883b-4ff6-9bcc-aaf1cc2f0fca"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          MW     LogP  NumHDonors  NumHAcceptors\n",
              "0    580.682  2.68582         3.0            8.0\n",
              "1    547.653  1.39862         4.0            8.0\n",
              "2    581.670  1.59522         4.0            8.0\n",
              "3    659.781  0.87060         6.0            9.0\n",
              "4    625.764  0.67400         6.0            9.0\n",
              "..       ...      ...         ...            ...\n",
              "209  668.767 -2.95720         4.0           10.0\n",
              "210  524.659  2.51690         3.0            7.0\n",
              "211  628.721 -1.81440         4.0           10.0\n",
              "212  468.551  0.95810         3.0            7.0\n",
              "213  572.613 -3.37320         4.0           10.0\n",
              "\n",
              "[214 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e24c28c3-4503-4145-a41a-2595d2e76290\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>MW</th>\n",
              "      <th>LogP</th>\n",
              "      <th>NumHDonors</th>\n",
              "      <th>NumHAcceptors</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>580.682</td>\n",
              "      <td>2.68582</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>547.653</td>\n",
              "      <td>1.39862</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>581.670</td>\n",
              "      <td>1.59522</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>659.781</td>\n",
              "      <td>0.87060</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>625.764</td>\n",
              "      <td>0.67400</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>209</th>\n",
              "      <td>668.767</td>\n",
              "      <td>-2.95720</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>524.659</td>\n",
              "      <td>2.51690</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>628.721</td>\n",
              "      <td>-1.81440</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>468.551</td>\n",
              "      <td>0.95810</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>572.613</td>\n",
              "      <td>-3.37320</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>214 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e24c28c3-4503-4145-a41a-2595d2e76290')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e24c28c3-4503-4145-a41a-2595d2e76290 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-e24c28c3-4503-4145-a41a-2595d2e76290');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-47bab459-1994-4d52-9f32-b3b48a7e6722\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-47bab459-1994-4d52-9f32-b3b48a7e6722')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-47bab459-1994-4d52-9f32-b3b48a7e6722 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_d834ab05-0b1d-4b57-adf7-dd5dc1ea73d6\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_lipinski')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_d834ab05-0b1d-4b57-adf7-dd5dc1ea73d6 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_lipinski');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Combining DataFrames**"
      ],
      "metadata": {
        "id": "UXllQIGkLZRx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_combined = pd.concat([df,df_lipinski], axis= 1)\n",
        "df_combined"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "Odue_2wuEwkK",
        "outputId": "47ef7849-14af-4060-9b61-70a338d32891"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    molecule_chembl_id                                   canonical_smiles  \\\n",
              "0         CHEMBL194398  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...   \n",
              "1         CHEMBL393608  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "2         CHEMBL238216  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "3         CHEMBL235873  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "4         CHEMBL397154  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "..                 ...                                                ...   \n",
              "209      CHEMBL4208764  CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...   \n",
              "210      CHEMBL4212620  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...   \n",
              "211      CHEMBL4216101  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...   \n",
              "212      CHEMBL4217568  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...   \n",
              "213      CHEMBL4204431  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...   \n",
              "\n",
              "     standard_value bioactivity_class       MW     LogP  NumHDonors  \\\n",
              "0          870000.0          inactive  580.682  2.68582         3.0   \n",
              "1          200000.0          inactive  547.653  1.39862         4.0   \n",
              "2          300000.0          inactive  581.670  1.59522         4.0   \n",
              "3           15000.0          inactive  659.781  0.87060         6.0   \n",
              "4           10000.0          inactive  625.764  0.67400         6.0   \n",
              "..              ...               ...      ...      ...         ...   \n",
              "209          4300.0      intermediate  668.767 -2.95720         4.0   \n",
              "210          5500.0      intermediate  524.659  2.51690         3.0   \n",
              "211          4100.0      intermediate  628.721 -1.81440         4.0   \n",
              "212          3200.0      intermediate  468.551  0.95810         3.0   \n",
              "213          8800.0               NaN  572.613 -3.37320         4.0   \n",
              "\n",
              "     NumHAcceptors  \n",
              "0              8.0  \n",
              "1              8.0  \n",
              "2              8.0  \n",
              "3              9.0  \n",
              "4              9.0  \n",
              "..             ...  \n",
              "209           10.0  \n",
              "210            7.0  \n",
              "211           10.0  \n",
              "212            7.0  \n",
              "213           10.0  \n",
              "\n",
              "[214 rows x 8 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-fcb36615-5004-44c5-b1e8-7b74dcae0cd7\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>canonical_smiles</th>\n",
              "      <th>standard_value</th>\n",
              "      <th>bioactivity_class</th>\n",
              "      <th>MW</th>\n",
              "      <th>LogP</th>\n",
              "      <th>NumHDonors</th>\n",
              "      <th>NumHAcceptors</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL194398</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...</td>\n",
              "      <td>870000.0</td>\n",
              "      <td>inactive</td>\n",
              "      <td>580.682</td>\n",
              "      <td>2.68582</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL393608</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>200000.0</td>\n",
              "      <td>inactive</td>\n",
              "      <td>547.653</td>\n",
              "      <td>1.39862</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL238216</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>300000.0</td>\n",
              "      <td>inactive</td>\n",
              "      <td>581.670</td>\n",
              "      <td>1.59522</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL235873</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>15000.0</td>\n",
              "      <td>inactive</td>\n",
              "      <td>659.781</td>\n",
              "      <td>0.87060</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL397154</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>10000.0</td>\n",
              "      <td>inactive</td>\n",
              "      <td>625.764</td>\n",
              "      <td>0.67400</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>209</th>\n",
              "      <td>CHEMBL4208764</td>\n",
              "      <td>CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...</td>\n",
              "      <td>4300.0</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>668.767</td>\n",
              "      <td>-2.95720</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>CHEMBL4212620</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...</td>\n",
              "      <td>5500.0</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>524.659</td>\n",
              "      <td>2.51690</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>CHEMBL4216101</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...</td>\n",
              "      <td>4100.0</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>628.721</td>\n",
              "      <td>-1.81440</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>CHEMBL4217568</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...</td>\n",
              "      <td>3200.0</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>468.551</td>\n",
              "      <td>0.95810</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>CHEMBL4204431</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...</td>\n",
              "      <td>8800.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>572.613</td>\n",
              "      <td>-3.37320</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>214 rows × 8 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fcb36615-5004-44c5-b1e8-7b74dcae0cd7')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-fcb36615-5004-44c5-b1e8-7b74dcae0cd7 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-fcb36615-5004-44c5-b1e8-7b74dcae0cd7');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-f5f29b90-6df8-4c4f-844a-804c3b208d10\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f5f29b90-6df8-4c4f-844a-804c3b208d10')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f5f29b90-6df8-4c4f-844a-804c3b208d10 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_33e59ce6-3fdb-4ac5-8c46-7bbe3769deee\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_combined')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_33e59ce6-3fdb-4ac5-8c46-7bbe3769deee button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_combined');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e0MLOedB6j96"
      },
      "source": [
        "### **Convert IC50 to pIC50**\n",
        "To allow **IC50** data to be more uniformly distributed, we will convert **IC50** to the negative logarithmic scale which is essentially **-log10(IC50)**.\n",
        "\n",
        "This custom function pIC50() will accept a DataFrame as input and will:\n",
        "* Take the IC50 values from the ``standard_value`` column and converts it from nM to M by multiplying the value by 10$^{-9}$\n",
        "* Take the molar value and apply -log10\n",
        "* Delete the ``standard_value`` column and create a new ``pIC50`` column"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "\n",
        "def pIC50(input):\n",
        "    pIC50 = []\n",
        "\n",
        "    for i in input['standard_value_norm']:\n",
        "        molar = i*(10**-9) # Converts nM to M\n",
        "        pIC50.append(-np.log10(molar))\n",
        "\n",
        "    input['pIC50'] = pIC50\n",
        "    x = input.drop('standard_value_norm', 1)\n",
        "\n",
        "    return x"
      ],
      "metadata": {
        "id": "1zgpwGKnMEwY"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_combined.standard_value.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kYN6NDHwwdx0",
        "outputId": "d0efaf73-10f9-4a00-9e32-2d69918b3d25"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count       214.000000\n",
              "mean      55138.037383\n",
              "std       96554.024824\n",
              "min         160.000000\n",
              "25%        8900.000000\n",
              "50%       28500.000000\n",
              "75%       50000.000000\n",
              "max      870000.000000\n",
              "Name: standard_value, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QyiJ0to5N6Z_",
        "outputId": "585c17f7-d973-4148-e88c-281d19b3621c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "-np.log10( (10**-9)* 100000000 )"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.0"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9S1aJkOYOP6K",
        "outputId": "2e4fbad9-e8bd-455f-e646-55641ecd1431",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "-np.log10( (10**-9)* 10000000000 )"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-1.0"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iktHDDwtPDwl"
      },
      "source": [
        "def norm_value(input):\n",
        "    norm = []\n",
        "\n",
        "    for i in input['standard_value']:\n",
        "        if i > 100000000:\n",
        "          i = 100000000\n",
        "        norm.append(i)\n",
        "\n",
        "    input['standard_value_norm'] = norm\n",
        "    x = input.drop('standard_value', 1)\n",
        "\n",
        "    return x"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "c-NI4aywUwzz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_norm = norm_value(df_combined)\n",
        "df_norm"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "N8xGPC3zUw9A",
        "outputId": "aa150b7d-17d3-47e0-b2d2-1d7505df6648"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-29-c8e03533cbc3>:10: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only.\n",
            "  x = input.drop('standard_value', 1)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    molecule_chembl_id                                   canonical_smiles  \\\n",
              "0         CHEMBL194398  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...   \n",
              "1         CHEMBL393608  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "2         CHEMBL238216  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "3         CHEMBL235873  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "4         CHEMBL397154  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "..                 ...                                                ...   \n",
              "209      CHEMBL4208764  CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...   \n",
              "210      CHEMBL4212620  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...   \n",
              "211      CHEMBL4216101  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...   \n",
              "212      CHEMBL4217568  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...   \n",
              "213      CHEMBL4204431  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...   \n",
              "\n",
              "    bioactivity_class       MW     LogP  NumHDonors  NumHAcceptors  \\\n",
              "0            inactive  580.682  2.68582         3.0            8.0   \n",
              "1            inactive  547.653  1.39862         4.0            8.0   \n",
              "2            inactive  581.670  1.59522         4.0            8.0   \n",
              "3            inactive  659.781  0.87060         6.0            9.0   \n",
              "4            inactive  625.764  0.67400         6.0            9.0   \n",
              "..                ...      ...      ...         ...            ...   \n",
              "209      intermediate  668.767 -2.95720         4.0           10.0   \n",
              "210      intermediate  524.659  2.51690         3.0            7.0   \n",
              "211      intermediate  628.721 -1.81440         4.0           10.0   \n",
              "212      intermediate  468.551  0.95810         3.0            7.0   \n",
              "213               NaN  572.613 -3.37320         4.0           10.0   \n",
              "\n",
              "     standard_value_norm  \n",
              "0               870000.0  \n",
              "1               200000.0  \n",
              "2               300000.0  \n",
              "3                15000.0  \n",
              "4                10000.0  \n",
              "..                   ...  \n",
              "209               4300.0  \n",
              "210               5500.0  \n",
              "211               4100.0  \n",
              "212               3200.0  \n",
              "213               8800.0  \n",
              "\n",
              "[214 rows x 8 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e60307e4-50f5-45fb-91cb-a942d3d17bc0\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>canonical_smiles</th>\n",
              "      <th>bioactivity_class</th>\n",
              "      <th>MW</th>\n",
              "      <th>LogP</th>\n",
              "      <th>NumHDonors</th>\n",
              "      <th>NumHAcceptors</th>\n",
              "      <th>standard_value_norm</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL194398</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>580.682</td>\n",
              "      <td>2.68582</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>870000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL393608</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>547.653</td>\n",
              "      <td>1.39862</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>200000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL238216</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>581.670</td>\n",
              "      <td>1.59522</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>300000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL235873</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>659.781</td>\n",
              "      <td>0.87060</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>15000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL397154</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>625.764</td>\n",
              "      <td>0.67400</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>10000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>209</th>\n",
              "      <td>CHEMBL4208764</td>\n",
              "      <td>CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>668.767</td>\n",
              "      <td>-2.95720</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>4300.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>CHEMBL4212620</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>524.659</td>\n",
              "      <td>2.51690</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5500.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>CHEMBL4216101</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>628.721</td>\n",
              "      <td>-1.81440</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>4100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>CHEMBL4217568</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>468.551</td>\n",
              "      <td>0.95810</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>3200.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>CHEMBL4204431</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>572.613</td>\n",
              "      <td>-3.37320</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8800.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>214 rows × 8 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e60307e4-50f5-45fb-91cb-a942d3d17bc0')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e60307e4-50f5-45fb-91cb-a942d3d17bc0 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-e60307e4-50f5-45fb-91cb-a942d3d17bc0');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-c4c846fa-2fa9-49c4-907d-b947cde536aa\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c4c846fa-2fa9-49c4-907d-b947cde536aa')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-c4c846fa-2fa9-49c4-907d-b947cde536aa button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_52eb3f6b-c950-4520-8c61-312f4329ab07\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_norm')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_52eb3f6b-c950-4520-8c61-312f4329ab07 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_norm');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_final = pIC50(df_norm)\n",
        "df_final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 458
        },
        "id": "RT_NdjzoVMr6",
        "outputId": "48ddbf63-3484-420d-cfc6-ce1c1a15c555"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-25-0aeeb04fb2d3>:11: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only.\n",
            "  x = input.drop('standard_value_norm', 1)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    molecule_chembl_id                                   canonical_smiles  \\\n",
              "0         CHEMBL194398  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...   \n",
              "1         CHEMBL393608  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "2         CHEMBL238216  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "3         CHEMBL235873  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "4         CHEMBL397154  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "..                 ...                                                ...   \n",
              "209      CHEMBL4208764  CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...   \n",
              "210      CHEMBL4212620  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...   \n",
              "211      CHEMBL4216101  CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...   \n",
              "212      CHEMBL4217568  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...   \n",
              "213      CHEMBL4204431  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...   \n",
              "\n",
              "    bioactivity_class       MW     LogP  NumHDonors  NumHAcceptors     pIC50  \n",
              "0            inactive  580.682  2.68582         3.0            8.0  3.060481  \n",
              "1            inactive  547.653  1.39862         4.0            8.0  3.698970  \n",
              "2            inactive  581.670  1.59522         4.0            8.0  3.522879  \n",
              "3            inactive  659.781  0.87060         6.0            9.0  4.823909  \n",
              "4            inactive  625.764  0.67400         6.0            9.0  5.000000  \n",
              "..                ...      ...      ...         ...            ...       ...  \n",
              "209      intermediate  668.767 -2.95720         4.0           10.0  5.366532  \n",
              "210      intermediate  524.659  2.51690         3.0            7.0  5.259637  \n",
              "211      intermediate  628.721 -1.81440         4.0           10.0  5.387216  \n",
              "212      intermediate  468.551  0.95810         3.0            7.0  5.494850  \n",
              "213               NaN  572.613 -3.37320         4.0           10.0  5.055517  \n",
              "\n",
              "[214 rows x 8 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5e80505f-1c0d-406f-b9f5-3033ec772a1a\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>canonical_smiles</th>\n",
              "      <th>bioactivity_class</th>\n",
              "      <th>MW</th>\n",
              "      <th>LogP</th>\n",
              "      <th>NumHDonors</th>\n",
              "      <th>NumHAcceptors</th>\n",
              "      <th>pIC50</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL194398</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>580.682</td>\n",
              "      <td>2.68582</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>3.060481</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL393608</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>547.653</td>\n",
              "      <td>1.39862</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>3.698970</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL238216</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>581.670</td>\n",
              "      <td>1.59522</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>3.522879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL235873</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>659.781</td>\n",
              "      <td>0.87060</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>4.823909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL397154</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>625.764</td>\n",
              "      <td>0.67400</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>209</th>\n",
              "      <td>CHEMBL4208764</td>\n",
              "      <td>CC(C)C[C@H](NC(=O)OC1(Cc2ccccc2)CCN(S(C)(=O)=O...</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>668.767</td>\n",
              "      <td>-2.95720</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.366532</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>CHEMBL4212620</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H](C=O)C[C@...</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>524.659</td>\n",
              "      <td>2.51690</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.259637</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>CHEMBL4216101</td>\n",
              "      <td>CCC1(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](C[C@@H]...</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>628.721</td>\n",
              "      <td>-1.81440</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.387216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>CHEMBL4217568</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@H]...</td>\n",
              "      <td>intermediate</td>\n",
              "      <td>468.551</td>\n",
              "      <td>0.95810</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.494850</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>CHEMBL4204431</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>572.613</td>\n",
              "      <td>-3.37320</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.055517</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>214 rows × 8 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5e80505f-1c0d-406f-b9f5-3033ec772a1a')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5e80505f-1c0d-406f-b9f5-3033ec772a1a button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-5e80505f-1c0d-406f-b9f5-3033ec772a1a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-39d79375-2d2f-4bc9-af52-7de052bb3694\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-39d79375-2d2f-4bc9-af52-7de052bb3694')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-39d79375-2d2f-4bc9-af52-7de052bb3694 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_664b4e5f-6c2f-4330-9244-c63c6edc5e8a\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_final')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_664b4e5f-6c2f-4330-9244-c63c6edc5e8a button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_final');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_final.pIC50.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lpQswx1U3CMn",
        "outputId": "abbbf374-eedd-41f4-c6e8-3eb49d951c2c"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    214.000000\n",
              "mean       4.635885\n",
              "std        0.619425\n",
              "min        3.060481\n",
              "25%        4.301030\n",
              "50%        4.545166\n",
              "75%        5.050691\n",
              "max        6.795880\n",
              "Name: pIC50, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "05vHBWvqaQtb"
      },
      "source": [
        "### **Removing the 'intermediate' bioactivity class**\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "Here, we will be removing the ``intermediate`` class from our data set."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_2class = df_final[df_final.bioactivity_class != 'intermediate']\n",
        "df_2class"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "Q6e_pPwd3ab_",
        "outputId": "4f9c33f0-c290-420f-a1f8-b30b450aec51"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    molecule_chembl_id                                   canonical_smiles  \\\n",
              "0         CHEMBL194398  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...   \n",
              "1         CHEMBL393608  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "2         CHEMBL238216  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "3         CHEMBL235873  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "4         CHEMBL397154  CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...   \n",
              "..                 ...                                                ...   \n",
              "198      CHEMBL3818400  CC(=O)N[C@@H](CC(=O)O)C(=O)N[C@@H](CO)C(=O)N[C...   \n",
              "200      CHEMBL3818000  CC(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](CO)C(=O)N[C...   \n",
              "203      CHEMBL4208240  CC(C)C[C@H](NC(=O)OC1CCN(C(=O)OC(C)(C)C)CC1)C(...   \n",
              "204      CHEMBL4209146  CC(C)C[C@H](NC(=O)OC1CCN(S(C)(=O)=O)CC1)C(=O)N...   \n",
              "213      CHEMBL4204431  CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...   \n",
              "\n",
              "    bioactivity_class       MW     LogP  NumHDonors  NumHAcceptors     pIC50  \n",
              "0            inactive  580.682  2.68582         3.0            8.0  3.060481  \n",
              "1            inactive  547.653  1.39862         4.0            8.0  3.698970  \n",
              "2            inactive  581.670  1.59522         4.0            8.0  3.522879  \n",
              "3            inactive  659.781  0.87060         6.0            9.0  4.823909  \n",
              "4            inactive  625.764  0.67400         6.0            9.0  5.000000  \n",
              "..                ...      ...      ...         ...            ...       ...  \n",
              "198          inactive  604.614 -4.32570        10.0           10.0  5.000000  \n",
              "200          inactive  577.548 -6.97880        11.0           11.0  5.124939  \n",
              "203          inactive  600.667 -2.59460         4.0           10.0  5.292430  \n",
              "204          inactive  474.580 -0.23880         3.0            7.0  4.540608  \n",
              "213               NaN  572.613 -3.37320         4.0           10.0  5.055517  \n",
              "\n",
              "[161 rows x 8 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e9e693d4-9054-4678-9573-30b969d8a1b0\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>molecule_chembl_id</th>\n",
              "      <th>canonical_smiles</th>\n",
              "      <th>bioactivity_class</th>\n",
              "      <th>MW</th>\n",
              "      <th>LogP</th>\n",
              "      <th>NumHDonors</th>\n",
              "      <th>NumHAcceptors</th>\n",
              "      <th>pIC50</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>CHEMBL194398</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@@H...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>580.682</td>\n",
              "      <td>2.68582</td>\n",
              "      <td>3.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>3.060481</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>CHEMBL393608</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>547.653</td>\n",
              "      <td>1.39862</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>3.698970</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CHEMBL238216</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>581.670</td>\n",
              "      <td>1.59522</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>3.522879</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CHEMBL235873</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>659.781</td>\n",
              "      <td>0.87060</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>4.823909</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>CHEMBL397154</td>\n",
              "      <td>CCOC(=O)/C=C/[C@H](C[C@@H]1CCNC1=O)NC(=O)[C@H]...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>625.764</td>\n",
              "      <td>0.67400</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>CHEMBL3818400</td>\n",
              "      <td>CC(=O)N[C@@H](CC(=O)O)C(=O)N[C@@H](CO)C(=O)N[C...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>604.614</td>\n",
              "      <td>-4.32570</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>CHEMBL3818000</td>\n",
              "      <td>CC(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](CO)C(=O)N[C...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>577.548</td>\n",
              "      <td>-6.97880</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>5.124939</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>CHEMBL4208240</td>\n",
              "      <td>CC(C)C[C@H](NC(=O)OC1CCN(C(=O)OC(C)(C)C)CC1)C(...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>600.667</td>\n",
              "      <td>-2.59460</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.292430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>CHEMBL4209146</td>\n",
              "      <td>CC(C)C[C@H](NC(=O)OC1CCN(S(C)(=O)=O)CC1)C(=O)N...</td>\n",
              "      <td>inactive</td>\n",
              "      <td>474.580</td>\n",
              "      <td>-0.23880</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>4.540608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>CHEMBL4204431</td>\n",
              "      <td>CCOC(=O)N1CCC(OC(=O)N[C@@H](CC(C)C)C(=O)N[C@@H...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>572.613</td>\n",
              "      <td>-3.37320</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.055517</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>161 rows × 8 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e9e693d4-9054-4678-9573-30b969d8a1b0')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e9e693d4-9054-4678-9573-30b969d8a1b0 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-e9e693d4-9054-4678-9573-30b969d8a1b0');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-d60d2d64-064f-4b00-975b-ee5120a5a511\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d60d2d64-064f-4b00-975b-ee5120a5a511')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d60d2d64-064f-4b00-975b-ee5120a5a511 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_3cb1158a-4132-41e7-9da2-94b0198fc2bd\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_2class')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_3cb1158a-4132-41e7-9da2-94b0198fc2bd button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('df_2class');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## **Exploratory Data Analysis**"
      ],
      "metadata": {
        "id": "zvk0JWCF31Lf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "sns.set(style = 'ticks')\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "UNwE2_yD37wA"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(5.5,5.5))\n",
        "\n",
        "sns.countplot(x='bioactivity_class', data= df_2class, edgecolor= 'black')\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize = 14, fontweight='bold')\n",
        "plt.ylabel('Frequency', fontsize = 14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_biactivity_class.pdf')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "id": "t2yOpDfq-ihN",
        "outputId": "e35e01ca-681f-4e6d-a970-c40ae2e13e09"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x550 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgEAAAHwCAYAAAA/wLxAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABCqUlEQVR4nO3de3zP9f//8ft7mPM2c5ZhW4xlMWEWTQ7FNsdCOjiUKIwosfxQygcdfPRxLEukklLSJxspNNE+FZFEThtmTjntYGNm798fu+z19bbN6f22ved1u14uXT7er+fz/Xo93vN5e933fD5fr5fFarVaBQAATMelqAsAAABFgxAAAIBJEQIAADApQgAAACZFCAAAwKQIAQAAmBQhAAAAkyIEAABgUiWLuoDipnnz5srMzFTVqlWLuhQAAPL4559/5Orqqi1btly3LyHgJl28eFGXL18u6jIAAMhXVlaWbvRmwE4XAg4dOqSFCxfqjz/+0L59++Tj46NVq1bl6ZeSkqJZs2ZpzZo1Sk5OVvXq1fXEE0/omWeeMfpkZmZq5syZ+u9//6vz588rMDBQEydOlI+Pzy3XV61aNUnSunXrbnkfAADcLh06dLjhvk4XAvbt26fY2Fg1adJE2dnZ+aaZ9PR09evXTyVKlND48eNVuXJlHTx4UGlpaTb9pkyZopiYGEVGRqp69ep67733NHDgQEVHR6tixYqF9ZEAAHBKThcC2rdvr44dO0qSIiMjtXPnzjx9FixYoPPnz+u///2vypUrJ0kKCgqy6XP8+HF9+eWXevXVV9WrVy9JUkBAgNq1a6dly5Zp8ODBt/mTAADg3Jzu6gAXl+uX9OWXX+rRRx81AkB+Nm3apOzsbHXu3NnY5uHhodatW2vjxo0OqRUAgOLM6ULA9Rw5ckT//POPKlWqpOeff16NGzdWy5YtNWHCBJ0/f97oFx8fr8qVK8vd3d3m/b6+voqPjy/ssgEAcDpONx1wPadOnZIkvfnmm3r44YcVFRWlgwcPasaMGUpPT9e///1vSTkLB/Ob93dzc1NycvI1j3GtRRXHjh1TzZo17fgEAAA4h2IXArKzsyVJ3t7eevPNNyVJwcHBKlmypCZMmKDRo0fLy8urKEsEAKBYKHYhIHd4/+qFgK1atZKUc3WBl5eX3Nzc8lwtIOWMEFw9RXC1a13+dzOXXgAA4MyK3ZoALy8vubq6Fth+8eJFSZKPj49OnTqVZ+g/Pj7ervsEAABwpyh2IcDV1VWtW7dWXFyczfaff/5ZknTPPfdIktq0aSMXFxetXbvW6JOcnKxNmzYpJCSk8AoGAMBJOd10QEZGhmJjYyVJSUlJSktL05o1ayRJLVu2lKenpyIiItS3b1+99NJL6tmzpw4dOqQZM2aoa9euqlOnjiSpRo0a6tWrl9566y25uLioevXqev/991WxYkX17du3yD4fAADOwmK90RsMF5IjR44UOO++ZMkSYy1AXFyc3nnnHe3du1fu7u7q2rWrRo8ebTNVkHvb4G+++Ubnz59Xs2bNNGHCBPn6+t5yfbm1cdtgAIAzupnzlNOFAGdHCAAAOLObOU8VuzUBAADAMQgBAACYFCEAAACTIgQAAGBShAAAAEzK6e4TYFaHDx82Ho4EOLMqVaoY9+MAULwRApzA4cOH1bBhQ2VkZBR1KcB1lS1bVn///TdBALgDEAKcwKlTp5SRkaHg8KFyq1yrqMsBCpRy+qjioufr1KlThADgDkAIcCJulWvJs7p3UZcBADAJFgYCAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApJwuBBw6dEiTJk1S9+7d5e/vry5dulyz/w8//CA/P798+6Wmpmr8+PFq2bKlAgMDNXLkSJ08efJ2lQ4AQLHidCFg3759io2NVd26deXr63vNvhcuXNDUqVNVpUqVfNtHjRqlzZs367XXXtM777yjhIQEDR48WFlZWbejdAAAipWSRV3A1dq3b6+OHTtKkiIjI7Vz584C+77//vuqVauWateunafftm3btGnTJi1cuFBt2rSRJHl7eyssLExr165VWFjY7fsQAAAUA043EuDicmMlHT58WIsWLdKECRPybd+4caPc3NzUunVrY5uPj48aNWqkjRs3OqRWAACKM6cLATfqX//6l7p3766GDRvm2x4fHy9vb29ZLBab7T4+PoqPjy+MEgEAcGpONx1wI9avX69t27ZpzZo1BfZJSUlRxYoV82x3d3e/5hSDJHXo0KHAtmPHjqlmzZo3XiwAAE6q2I0EXLx4UVOnTtWIESPk6elZ1OUAAFBsFbuRgI8++kguLi4KDw9XSkqKJOnSpUvKzs5WSkqKypQpI1dXV7m5uen48eN53p+cnCx3d/drHmPdunUFtl1rlAAAgOKk2IWA+Ph4HTp0SMHBwXnaWrRooddee02PP/64fHx8FBcXJ6vVarMuICEhQQ0aNCjMkgEAcErFLgQMHjxYPXv2tNm2YMECJSQkaNq0aapXr54kKSQkRPPmzVNcXJzuv/9+STkBYNeuXXr22WcLu2wAAJyO04WAjIwMxcbGSpKSkpKUlpZmLABs2bKlfH1989xE6Ouvv9aJEycUFBRkbAsMDFSbNm00fvx4jRs3TqVLl9bMmTPl5+enhx9+uPA+EAAATsrpQsDp06f1wgsv2GzLfb1kyRKbE/31vPvuu5o2bZomTZqkrKwstWnTRhMmTFDJkk73sQEAKHROdzasXbu29uzZc1PvmT59er7bK1asqKlTp2rq1KmOKA0AgDtKsbtEEAAAOAYhAAAAkyIEAABgUoQAAABMihAAAIBJEQIAADApQgAAACZFCAAAwKQIAQAAmBQhAAAAkyIEAABgUoQAAABMihAAAIBJEQIAADApQgAAACZFCAAAwKQIAQAAmBQhAAAAkyIEAABgUoQAAABMihAAAIBJEQIAADApQgAAACZFCAAAwKQIAQAAmBQhAAAAkyIEAABgUoQAAABMihAAAIBJEQIAADApQgAAACZFCAAAwKQIAQAAmBQhAAAAkyIEAABgUoQAAABMihAAAIBJEQIAADApQgAAACZVsqgLuNqhQ4e0cOFC/fHHH9q3b598fHy0atUqoz0tLU2LFi1SbGysDh48KFdXV917770aPXq0/Pz8bPaVmpqqadOm6YcfftClS5f0wAMPaMKECapWrVphfywAAJyO040E7Nu3T7Gxsapbt658fX3ztB89elSff/65WrdurXfffVdvvPGGUlNT9dhjj+nAgQM2fUeNGqXNmzfrtdde0zvvvKOEhAQNHjxYWVlZhfVxAABwWk43EtC+fXt17NhRkhQZGamdO3fatNeuXVvff/+9ypYta2xr1aqV2rdvr6VLl2rixImSpG3btmnTpk1auHCh2rRpI0ny9vZWWFiY1q5dq7CwsEL6RAAAOCenGwlwcbl2SeXKlbMJAJJUvnx51alTRydPnjS2bdy4UW5ubmrdurWxzcfHR40aNdLGjRsdWzQAAMWQ04WAW5GSkmKsH8gVHx8vb29vWSwWm74+Pj6Kj48v7BIBAHA6TjcdcCvefvttWSwWPf7448a2lJQUVaxYMU9fd3f3PFMMV+vQoUOBbceOHVPNmjVvvVgAAJxEsQ8BX331lb744gtNnz5dNWrUKOpyAAAoNop1CIiNjdWkSZM0bNgw9ezZ06bNzc1Nx48fz/Oe5ORkubu7X3O/69atK7DtWqMEAAAUJ8V2TcD27dv1wgsvqEePHnrhhRfytPv4+CghIUFWq9Vme0JCgs3aAQAAzKpYhoD9+/frueeeU6tWrTR58uR8+4SEhCg5OVlxcXHGtoSEBO3atUshISGFVSoAAE7L6aYDMjIyFBsbK0lKSkpSWlqa1qxZI0lq2bKlrFarBg0apNKlS2vAgAE2i/wqVKigu+++W5IUGBioNm3aaPz48Ro3bpxKly6tmTNnys/PTw8//HDhfzAAAJyM04WA06dP5xnez329ZMkSSTLm+gcOHGjTr2XLlvr444+N1++++66mTZumSZMmKSsrS23atNGECRNUsqTTfWwAAAqd050Na9eurT179lyzz/Xac1WsWFFTp07V1KlTHVEaAAB3lGK5JgAAANiPEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTcroQcOjQIU2aNEndu3eXv7+/unTpkm+/5cuXq1OnTgoICFC3bt20YcOGPH1SU1M1fvx4tWzZUoGBgRo5cqROnjx5uz8CAADFgl0hoEuXLlq0aJFOnz7tqHq0b98+xcbGqm7duvL19c23T3R0tCZOnKjQ0FBFRUWpadOmioiI0Pbt2236jRo1Sps3b9Zrr72md955RwkJCRo8eLCysrIcVi8AAMVVSXvevH//fr311luaMWOGQkJC9Mgjj6hdu3YqUaLELe+zffv26tixoyQpMjJSO3fuzNNn1qxZCg8P16hRoyRJrVq10t69ezV37lxFRUVJkrZt26ZNmzZp4cKFatOmjSTJ29tbYWFhWrt2rcLCwm65RgAA7gQOmQ7IysrShg0bNGLECIWEhOjNN9/U/v37b60gl2uXlJiYqIMHDyo0NNRme1hYmOLi4pSZmSlJ2rhxo9zc3NS6dWujj4+Pjxo1aqSNGzfeUm0AANxJ7AoBTz/9tGrWrClJslqtslqtOnPmjBYvXqyuXbuqd+/eWrZsmdLS0hxSrCTFx8dLyvmt/kq+vr66dOmSEhMTjX7e3t6yWCw2/Xx8fIx9AABgZnZNB4wbN07jxo3Tjh07tHr1an333Xc6evSo0f7nn39q586dmj59ujp27Kgnn3xSgYGBdhWcnJwsSXJzc7PZnvs6tz0lJUUVK1bM8353d/d8pxiu1KFDhwLbjh07ZgQfAACKM4dMB9x7770aN26c1q9fry+++EIDBw5U6dKlZbFYZLVadeHCBUVHR+uJJ57Qiy++aAzZAwCAomPXSMDV/vnnH8XFxWn9+vXGiT43CFitVknS6tWr5eXlpdGjR9/SMdzd3SXlXP5XtWpVY3tKSopNu5ubm44fP57n/cnJyUafgqxbt67AtmuNEgAAUJzYPRJgtVq1YcMGDRs2TO3atdO7775rzMtbrVa5urrq0Ucf1YsvvigPDw9ZrVZ9++23t3w8Hx8fScozrx8fH69SpUrJy8vL6JeQkGCEj1wJCQnGPgAAMDO7RgJmzpyplStXGjfgufKEW6tWLfXt21d9+vSRh4eHJKlq1ap65ZVXdOLEiVs+ppeXl+rVq6c1a9YYlxJKUkxMjIKDg+Xq6ipJCgkJ0bx58xQXF6f7779fUk4A2LVrl5599tlbPj4AAHcKu0LA+++/bwz352rZsqX69eunDh065Lncr1atWpKk7OzsAveZkZGh2NhYSVJSUpLS0tK0Zs0aY9+enp4aMWKExowZozp16igoKEgxMTHasWOHPvnkE2M/gYGBatOmjcaPH69x48apdOnSmjlzpvz8/PTwww/b87EBALgj2L0mwGq1qmzZsurataueeuopNWjQoMC+vr6+mjZt2jX3d/r0ab3wwgs223JfL1myREFBQerSpYsyMjIUFRWlBQsWyNvbW3PmzMlz5cG7776radOmadKkScrKylKbNm00YcIElSzp0KUQAAAUS3adDWvXrq0nnnhCvXr1ynPJXn6qVKminj17Xnefe/bsue6+evfurd69e1+zT8WKFTV16lRNnTr1uvsDAMBs7AoB33//fZ6b8QAAgOLBrhBw5MgR7d27V1LOHLynp6fRdubMGW3btk2S1KBBA2PVPgAAcA52hYB58+Zp5cqV8vDwyPMo3/Lly+u1117TqVOn1KNHj+uuBQAAAIXLrvsE/P7775Kkdu3aqUyZMjZtpUuXVrt27WS1WrV161Z7DgMAAG4Du0JA7v0BateunW97jRo1JOXcSRAAADgXu0JA7v0Brnxo0JVyt1991z4AAFD07AoB1apVk9VqVXR0tA4fPmzTdvjwYUVHR8tisahatWp2FQkAABzProWB9913nw4fPqyMjAz16NFDPXr0UO3atXXkyBF98803ysjIkMVi0X333eeoegEAgIPYFQKeeOIJrVy5UpKUnp6uzz77zGjLnQKwWCx64okn7DkMAAC4DeyaDggICNDw4cNltVoLvGnQ8OHDFRAQYM9hAADAbWD3TfQjIiLk6+urqKgo7d692wgE/v7+GjJkiDp37uyIOgEAgIM55Ek6oaGhCg0N1YULF5ScnCx3d/c89w0AAADOxaGP0ytTpgwnfwAAigmHhIAdO3bozz//VHJysrKzs/PtExER4YhDAQAAB7ErBKSkpGj48OHasmXLdfsSAgAAcC52hYC33npLv/32m6ScSwELujMgjxsGAMD52BUC1q9fb5z8XVxcVKlSJbm6ujqqNgAAcBvZFQLS0tIkSX5+flqyZInc3d0dUhQAALj97LpZUL169SRJHTt2JAAAAFDM2BUCHnvsMVmtVm3fvt1B5QAAgMJi13RASEiI7rvvPv38888aOXKkHn/8cd11110qWTLvbmvVqmXPoQAAgIPZFQIeeughY2Hg999/r++//z7ffhaLRbt27bLnUAAAwMEccrOg3EsAC7pEEAAAOB+7QwAnfgAAiie7QsCSJUscVQcAAChkdoWAli1bOqoOAABQyOy6RPBqFy9e1IkTJ3T+/HlH7hYAANwGDlkYGB0drYULF+rvv/+W1WrV2LFjVb9+fUVHR8tisSgyMlJubm6OOBQAAHAQu0PAm2++qcWLF0vKWSSYe6WAt7e3vv76a1ksFgUGBqp37972HgoAADiQXdMBsbGxWrRokaS8Vwncdddd8vf3lyRt3rzZnsMAAIDbwK4QsHTpUkk59wl44okn8rQ3adJEVqtVu3fvtucwAADgNrArBOzYsUMWi0WdO3fWpEmT8rRXr15dknTy5El7DgMAAG4Du0JAamqqJKlBgwb5tl+8eFGSdOnSJXsOAwAAbgO7QkDuiv9Dhw7l275t2zZJkoeHhz2HAQAAt4FdIaBRo0ayWq2Kjo7W119/bWw/efKkZsyYof/973+yWCxq3Lix3YUCAADHsusSwa5du2rz5s26dOmSxo8fLynnKoHcSwZzdevWzZ7DAACA28CukYDu3bsrODjYuDzQYrEY9wnIdf/99yssLMyewwAAgNvArhBgsVj03nvvqU+fPipRooSsVqvxn4uLi/r06aO5c+c6qlYAAOBAdt8xsHTp0nr99df10ksv6Y8//lBycrLc3d3VpEkTubu7O6JGAABwGzjk2QGS5O7urpCQEEft7rrWrVun9957T/v371f58uV13333acyYMfLy8rLpt3z5cn3wwQc6evSovL29NXr0aLVr167Q6gQAwFnZFQKOHj16w31r1aplz6Fs/PLLL4qIiFCPHj00evRonTt3Tv/5z3/0zDPP6Ntvv1WZMmUk5TzYaOLEiXr++efVqlUrxcTEKCIiQp9++qmaNm3qsHoAACiO7AoB7du3z7MQMD8Wi0W7du2y51A2oqOjVatWLU2dOtU4vqenpwYMGKCdO3eqefPmkqRZs2YpPDxco0aNkiS1atVKe/fu1dy5cxUVFeWwegAAKI7sWhiY68oFgQX950hZWVkqX768TQCpWLGiUYskJSYm6uDBgwoNDbV5b1hYmOLi4pSZmenQmgAAKG7sDgEFneDzu1zQUR555BEdOHBAn376qVJTU5WYmKh///vf8vf3V7NmzSRJ8fHxknIeaXwlX19fXbp0SYmJibelNgAAigu7pgOWLFmSZ1tmZqYOHTqkTz/9VAkJCXrwwQf1zDPP2HOYPJo3b645c+bopZde0uuvvy4p5+6FH3zwgUqUKCFJSk5OlvR/tzbOlfs6tz0/HTp0KLDt2LFjqlmzpl31AwDgDOwKAS1btsx3e5s2bdStWzd16dJFsbGx6tOnjz2HyeP333/X2LFj1adPHz344IM6d+6c5s2bpyFDhmjp0qXGwkAAAFAwh10ieLWKFSuqWbNmWr16tRYsWKD27ds7bN9TpkxRq1atFBkZaWxr2rSpHnzwQX3zzTd67LHHjHsUpKamqmrVqka/lJQUSbrmPQzWrVtXYNu1RgkAAChOHLIwMD9paWnasWOHJOnvv/926L4PHDighg0b2myrUaOGKlWqpMOHD0uSfHx8JP3f2oBc8fHxKlWqVJ77CQAAYDZ2jQT0798/zzar1aqLFy8qISFBaWlpknLuKuhItWrVynPJYVJSks6ePau77rpLkuTl5aV69eppzZo16tixo9EvJiZGwcHBcnV1dWhNAAAUN3aFgF9//bXAKwCsVqtxhUDr1q3tOUweffv21dSpUzVlyhS1b99e586d0/z581W5cmWbSwJHjBihMWPGqE6dOgoKClJMTIx27NihTz75xKH1AABQHNm9JuBa9wCwWq2qW7euxo0bZ+9hbPTv31+urq767LPP9NVXX6l8+fJq2rSp3n33XVWqVMno16VLF2VkZCgqKkoLFiyQt7e35syZo8DAQIfWAwBAcWRXCOjZs2e+2y0Wi9zc3BQQEKCHHnrI4UPvFotFjz/+uB5//PHr9u3du7d69+7t0OMDAHAnsCsETJs2zVF1AACAQnbbrg4AAADOza6RgN9+++2W39uiRQt7Dg0AAOxkVwjo16/fLT0fwNFPFQQAADfPIXcMvNGnBFosFoc/URAAANwahzxFsKDRgKu3EwAAAHAedo0E/PDDD/rXv/6lDRs2qE+fPurWrZsqV66s06dP65tvvtHy5cv14IMPasKECbftscIAAODW2BUCNm3apB9//FEPP/yw8UhfSfL29lbz5s117tw5/fDDD3rggQf05JNP2l0sAABwHLumA3Jvv1u/fv182xs0aCCr1aqlS5facxgAAHAb2BUCcp/Yt2HDBl26dMmm7dKlS9qwYYMkKTEx0Z7DAACA28Cu6QBPT0+dOHFCu3fvVpcuXdSpUyd5enrqzJkz+u6774yQ4Onp6ZBiAQCA49gVAsLDw7Vw4UJZLBYdOnRIUVFRRlvulQAWi0VdunSxr0oAAOBwdk0HREREKDAw8JqXCTZt2lQRERH2HAYAANwGdoWAsmXL6uOPP9aYMWNUt25dWa1W4z9vb2+9/PLL+vjjj1WmTBlH1QsAABzE7jsGlixZUs8++6yeffZZnT9/XmlpaapQoYLKly/viPoAAMBt4pDbBucqX748J38AAIoJh4SAbdu2adGiRfr999919uxZjRkzRk2aNNHPP/8sSXr22WeZEgAAwMnYHQKWLFmi6dOnG2sBchcIurm5ac6cObJYLPL29lZ4eLjdxQIAAMexa2Hg9u3bbQLAle6++275+PhIkjZu3GjPYQAAwG1gVwhYtGiRsrOzJUlt27bN096sWTNZrVbt3LnTnsMAAIDbwK4QsHXrVlksFj3wwAN6//3387TXqlVLknTs2DF7DgMAAG4Du0LAuXPnJOX8xp+f3FGCzMxMew4DAABuA7tCQO7lgCdOnMi3/a+//pKUs0gQAAA4F7tCQP369WW1WvXtt9/q119/NbZfuHBBy5YtU2xsrCwWi/z8/OwuFAAAOJZdlwh27txZW7Zs0fnz5zVgwABJOQ8OmjVrlvFni8Wizp07218pAABwKLtGAvr06aOGDRvaPDHQYrHYXC7YqFEjPfroo/ZVCQAAHM6uEODq6qoPP/xQrVu3tnl4kJQzCtC6dWt98MEHKlnSoXcnBgAADmD32dnT01MLFy7Unj179Pvvvys5OVnu7u4KDAxUw4YNHVEjAAC4DW45BKSlpWn27NmSpLvuukv9+/dnASAAAMXILYeAChUq6NNPP9Xly5c1cOBAB5YEAAAKg11rAmrUqCFJKlu2rEOKAQAAhceuEBAeHi6r1Wo8MhgAABQfdoWAoUOHqnnz5vrjjz/0wgsvaNeuXbpw4YKjagMAALeRXVcHBAYGSsq5HHDt2rVau3Ztvv0sFot27dplz6EAAICD2RUCcu8IaLFYjNcAAKB4sPs+AZz4AQAonuwKAdOmTXNUHQAAoJDddAh45ZVXJOVcGdCzZ09J0vHjx5WYmChJatGihQPLAwAAt8tNh4Cvv/5aFotFDRo0UJs2bSRJMTExevvtt1kACABAMWLXJYJXuvLhQYXl66+/Vo8ePRQQEKCgoCA9++yzNpcorl+/Xt26dVNAQIA6deqkr776qlDrAwDAmRXbx/vNnz9fUVFRev7559W0aVOdPXtWcXFxunz5siRpy5YtioiIUK9evTR+/Hj973//0//7f/9P5cuXV+fOnYu4egAAil6xDAHx8fGaM2eO5s2bp7Zt2xrbO3XqZPx5/vz5uvfee/X6669Lklq1aqXExETNmjWLEAAAgBw4HVCYVqxYodq1a9sEgCtlZmbql19+yXOyDwsL04EDB3TkyJHCKBMAAKd2yyMBO3fu1MqVK40/58rddrUePXrc6qHy+OOPP9SgQQPNmzdPH3/8sVJTU9W4cWO98soratKkiQ4fPqxLly7Jx8fH5n2+vr6SckYSateu7bB6AAAojm45BMTExCgmJsZmm9VqNS4hvJojQ8A///yjnTt3au/evXr11VdVtmxZvffee3rmmWe0du1aJScnS5Lc3Nxs3pf7Ore9IB06dCiw7dixY6pZs6adnwAAgKJn922DJRV462CLxWLcWtiRrFar0tPT9Z///EcNGzaUJDVp0kTt27fXJ598Yly6CAAACnZLIeDqSwELujTwdl0y6ObmJg8PDyMASJKHh4f8/f21f/9+hYeHS5JSU1Nt3peSkiJJcnd3v+b+161bV2DbtUYJAAAoTm46BCxZsuR21HFT7r77bh0+fDjftosXL6pOnToqVaqU4uPj9cADDxht8fHxkpRnrQAAAGZ00yGgZcuWt6OOm9KuXTutWLFCu3fvVqNGjSRJZ8+e1V9//aWBAwfK1dVVQUFB+u677zRgwADjfTExMfL19WVRIAAAKqb3CejYsaMCAgI0cuRIjR49WqVLl9aCBQvk6uqqJ554QpI0dOhQ9e/fX6+99ppCQ0P1yy+/aNWqVZo5c2YRVw8AgHMolvcJcHFx0YIFC9S0aVNNmjRJL774oipUqKBPP/1UVatWlSQ1b95cs2fP1tatWzVo0CCtWrVKU6ZMUWhoaBFXDwCAcyiWIwGS5OnpqbfffvuafTp06MBCPgAAClAsRwIAAID9CAEAAJgUIQAAAJMiBAAAYFKEAAAATIoQAACASRECAAAwKUIAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEAAAATIoQAACASRECAAAwKUIAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEAAAATIoQAACASRECAAAwKUIAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEAAAATIoQAACASRECAAAwKUIAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEAAAATIoQAACASRECAAAwqTsiBJw/f14hISHy8/PTn3/+adO2fPlyderUSQEBAerWrZs2bNhQRFUCAOBc7ogQMG/ePF2+fDnP9ujoaE2cOFGhoaGKiopS06ZNFRERoe3btxd+kQAAOJliHwIOHDigpUuXasSIEXnaZs2apfDwcI0aNUqtWrXS66+/roCAAM2dO7cIKgUAwLkU+xAwZcoU9e3bV97e3jbbExMTdfDgQYWGhtpsDwsLU1xcnDIzMwuzTAAAnE6xDgFr1qzR3r17NXz48Dxt8fHxkpQnHPj6+urSpUtKTEwslBoBAHBWJYu6gFuVkZGh6dOna/To0apQoUKe9uTkZEmSm5ubzfbc17nt+enQoUOBbceOHVPNmjVvpWQAAJxKsR0JmD9/vipXrqxHH320qEsBAKBYKpYjAUlJSfrwww81d+5cpaamSpLS09ON/z1//rzc3d0lSampqapatarx3pSUFEky2vOzbt26AtuuNUoAAEBxUixDwJEjR3Tp0iUNGTIkT1v//v3VpEkTzZgxQ1LO2gAfHx+jPT4+XqVKlZKXl1eh1QsAgDMqliGgUaNGWrJkic223bt3a9q0aZo8ebICAgLk5eWlevXqac2aNerYsaPRLyYmRsHBwXJ1dS3ssgEAcCrFMgS4ubkpKCgo37Z77rlH99xzjyRpxIgRGjNmjOrUqaOgoCDFxMRox44d+uSTTwqzXAAAnFKxDAE3qkuXLsrIyFBUVJQWLFggb29vzZkzR4GBgUVdGgAARe6OCQFBQUHas2dPnu29e/dW7969i6AiAACcW7G9RBAAANiHEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAAGBShAAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTKpYhYPXq1Ro6dKhCQkLUtGlTde/eXV9++aWsVqtNv+XLl6tTp04KCAhQt27dtGHDhiKqGAAA51MsQ8DixYtVtmxZRUZGav78+QoJCdHEiRM1d+5co090dLQmTpyo0NBQRUVFqWnTpoqIiND27duLrnAAAJxIyaIu4FbMnz9fnp6exuvg4GCdO3dOixYt0rBhw+Ti4qJZs2YpPDxco0aNkiS1atVKe/fu1dy5cxUVFVVElQMA4DyK5UjAlQEgV6NGjZSWlqb09HQlJibq4MGDCg0NtekTFhamuLg4ZWZmFlapAAA4rWIZAvKzdetWVa9eXRUqVFB8fLwkydvb26aPr6+vLl26pMTExKIoEQAAp1IspwOutmXLFsXExGjcuHGSpOTkZEmSm5ubTb/c17ntBenQoUOBbceOHVPNmjXtKRcAAKdQ7EcCjh8/rtGjRysoKEj9+/cv6nIAACg2ivVIQEpKigYPHiwPDw/Nnj1bLi45mcbd3V2SlJqaqqpVq9r0v7K9IOvWrSuw7VqjBAAAFCfFdiTgwoULeu6555SamqoPPvhAFStWNNp8fHwkyVgbkCs+Pl6lSpWSl5dXodYKAIAzKpYhICsrS6NGjVJ8fLw++OADVa9e3abdy8tL9erV05o1a2y2x8TEKDg4WK6uroVZLgAATqlYTgdMnjxZGzZsUGRkpNLS0mxuAOTv7y9XV1eNGDFCY8aMUZ06dRQUFKSYmBjt2LFDn3zySdEVDgCAEymWIWDz5s2SpOnTp+dpW7dunWrXrq0uXbooIyNDUVFRWrBggby9vTVnzhwFBgYWdrkAADilYhkC1q9ff0P9evfurd69e9/magAAKJ6K5ZoAAABgP0IAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEAAAATIoQAACASRECAAAwKUIAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEAAAATIoQAACASRECAAAwKUIAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEAAAATIoQAACASRECAAAwKUIAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEAAAATKpkURcAALfD4cOHderUqaIuA7iuKlWqqE6dOkVybEIAgDvO4cOH1ahhQ6VnZBR1KcB1lStbVrv//rtIggAhAMAd59SpU0rPyNAbfdvKu5pHUZcDFCjh5DlNXBarU6dOEQIAwJG8q3mo4V1ViroMwGmxMBAAAJMiBAAAYFKEAAAATIoQAACASd3xIeDAgQN6+umn1bRpU7Vu3VpvvfWWMjMzi7osAACK3B19dUBycrIGDBigevXqafbs2Tpx4oSmT5+uCxcuaNKkSUVdHgAAReqODgHLli3T+fPnNWfOHHl4eEiSLl++rMmTJ+u5555T9erVi7ZAAACK0B09HbBx40YFBwcbAUCSQkNDlZ2drc2bNxddYQAAOIE7OgTEx8fLx8fHZpubm5uqVq2q+Pj4IqoKAADncEdPB6SkpMjNzS3Pdnd3dyUnJxf4vg4dOhTYduTIEZUoUeKafW5WZmam6tWrp0NbliuxxB39V4JiLvtylurVq6cXXnhBrq6uRV1OgXK/U/9ev1clS+wv6nKAAmVdznb4d+rYsWMqUaLEDfXljHOTLBaLSpZ07I/N1dU1z4gF7HPs2DFJUs2aNYu4kjuR89+Gl++U4/Gdun08qjl2fyVLlrzhQHFHhwA3Nzelpqbm2Z6cnCx3d/cC37du3brbWRYKQe5IDX+XgGPwnboz3dFrAnx8fPLM/aempuqff/7htwQAgOnd0SEgJCREP//8s1JSUoxta9askYuLi1q3bl2ElQEAUPTu6BDQt29flS9fXsOHD9emTZv01Vdf6a233lLfvn25RwAAwPTu6BDg7u6ujz76SCVKlNDw4cM1Y8YM9erVS5GRkUVdGgAARe6OXhgoSb6+vlq8eHFRlwEAgNO5o0cCAABAwSxWq9Va1EUAAIDCx0gAAAAmRQgAAMCkCAEAAJgUIQAAAJMiBAAAYFKEABSKyMhIdenSpUiOvXjxYsXGxubZ3r59e73++utFUBFQPKxYsULffvttnu39+vXTc889VwQVwdG4RBCF4vDhw0pPT1fDhg0L/djt27fXgw8+qEmTJtls37Vrl9zc3FS7du1CrwkoDvr166dy5crp/ffft9m+f/9+ubi48CC2O8Adf8dAOIc6deoUdQl5+Pv7F3UJQLF09913F3UJcBCmA1AorpwOWLFihfz8/LRr1y49++yzatq0qR5++GGtXLnS5j0//vijnn76aQUHB6tZs2bq3bu3Nm7cmGffJ06c0NixY3X//ffr3nvvVefOnfXRRx9JyhkFSEpK0qeffio/Pz/5+flpxYoVRlvudMCKFSvk7++vU6dO2ez73Llzaty4sZYtW2Zs27Ztm/r376+mTZvqvvvu00svvaTTp0877GcFOMK2bdv0/PPPq02bNmratKm6d++e5zuWkpKiN954QyEhIWrcuLHat2+vGTNmSMoZBfj111/1448/Gt+d2bNnG2250wG//PKL/Pz89Oeff9rs+/Lly2rdurWxP0k6cOCAhg4dqvvuu09NmzbVkCFDdPjw4dv4U8D1MBKAIjNmzBj16dNHTz/9tL744gtFRkYqICBAvr6+kqQjR46oXbt2euaZZ+Ti4qKNGzdqyJAh+uijjxQUFCRJOnv2rB577DFJ0ujRo1W7dm0dOnTI+Idlzpw5GjJkiJo1a6ZnnnlGUv6jEg899JBeffVVrVmzRk899ZSxfe3atZKkzp07S8r5h7Vfv35q27atZs6cqYyMDL377rsaNmyYPv/889v0kwJu3tGjR9WsWTM9/vjjcnV11e+//64JEybIarWqZ8+eyszM1IABA5SUlKThw4erQYMGOn78uLZu3SpJevXVV/Xyyy+rTJkyGjdunCSpRo0aeY7TokULVatWTTExMQoICDC2/+9//9OpU6eM8J+YmKi+ffuqfv36mj59uiwWi9577z0NHDhQa9askaurayH8VHA1QgCKzJNPPqknn3xSkhQYGKjY2Fh99913GjZsmCTZnIyzs7MVFBSk/fv364svvjBCwOLFi3X69GmtXr3amNsPDg423ufv7y9XV1dVqVJFTZs2LbCWihUrqm3btlq1apXNcVetWqXWrVvLw8NDkjRjxgw1btxYc+bMkcVikSQ1aNBAXbp0UWxsrNq2bWv/DwZwgPDwcOPPVqtVLVq00IkTJ/T555+rZ8+eWrlypXbt2qVly5YpMDDQ6NuzZ09JOUP+FSpUULly5a753XFxcVFYWJhiYmI0duxY43uxatUq1a9fX35+fpJyArm7u7sWLVqk0qVLS5KaNWumDh06aPny5ca/BShcTAegyLRp08b4c7ly5VSrVi0dP37c2Hb8+HGNGzdODzzwgPz9/XXPPfdo06ZNSkhIMPrExcWpVatWDlncFx4eru3bt+vo0aOSpJMnT+q3334z/jHNyMjQ77//rs6dO+vy5cvKyspSVlaW6tWrp5o1a+YZDgWKUnJysqZMmaJ27drpnnvu0T333KPPP//c+P7ExcXJ19fXJgDcqvDwcJtRhMzMTP3www82QWTz5s1q3769SpQoYXx33Nzc5O/vr507d9pdA24NIwEoMhUrVrR5XapUKWVmZkrK+c1/6NChSk1N1ciRI1W3bl2VLVtWs2bN0rFjx4z3nDt3TvXr13dIPe3atVPZsmUVHR2twYMHa/Xq1SpdurQ6duwoKWf+9PLly5o2bZqmTZuW5/1X1gUUtcjISG3btk3Dhw83fqv/7LPPtHr1akk5351q1ao55Fj33nuv6tSpo1WrVql58+bauHGjUlJSbC4LPnv2rD766CNjvc6VSpUq5ZA6cPMIAXBKhw4d0q5duzR37lzjJCxJFy5csOnn4eGhkydPOuSYZcqUUceOHRUTE6PBgwcrJiZG7dq1U7ly5STlhBaLxaLnnnvOpqZclSpVckgdgL0uXryoH3/8UZGRkerXr5+xfenSpcafPTw8tGfPHocdMzw8XJ9//rkmTJigmJgYNWnSRF5eXka7u7u72rZtqyeeeCLPe8uXL++wOnBzCAFwShcvXpRk+xtCUlKStm3bpnr16hnbgoOD9eGHH+ro0aOqVatWvvsqVaqUsb/r6dKli4YMGaKffvpJ27dv1+DBg4223LnR+Ph4mwVQgLPJzMxUdna2zfcnLS1N69evN17ff//9iomJ0R9//KEmTZrku5+b/e7Mnz9f69ev1/r16zV69Gib9uDgYO3bt0/+/v4qUaLELXwq3A6EADglHx8f1ahRQzNmzFB2drbS09M1a9asPMOXAwcO1DfffKOnnnpKQ4cOlZeXlxITE3Xw4EG9/PLLxr7+97//afPmzcbNgQr6rf3++++Xh4eHxo8fLzc3N4WEhNi0jx07VgMGDNCoUaMUHh4uNzc3HT9+XD///LMeeeQRY8EiUJQqVqyogIAARUVFydPTUyVLltSCBQtUoUIFnTlzRpLUvXt3LV26VEOGDFFERITq16+vEydOaMuWLXrjjTck5Xx3Vq5cqfXr16tq1aqqVq2aqlevnu8x7777bvn5+emNN97QxYsXFRYWZtM+cuRI9erVS4MGDVKfPn1UpUoVnTp1Sr/++quaN29eZHcUNTsWBsIpubq6avbs2XJ1ddULL7ygWbNmaejQoWrZsqVNv0qVKumzzz5Ts2bN9M4772jIkCH68MMPbS5levHFF1WjRg2NGDFCvXr10oYNGwo8bqlSpdSpUyedPHlSDz/8cJ7Llpo1a6alS5cqPT1dr7zyioYMGaJ58+apTJkyqlu3rmN/CIAdZsyYoTp16igyMlJTpkxRp06d1KNHD6Pd1dVVixcvVmhoqN5//309++yzmj17tjw9PY0+gwcPVrNmzTRu3Dj16tVLX3zxxTWP2aVLF508eVJBQUGqWrWqTVvdunW1fPlyeXh4aPLkyRo0aJDeeecdZWRkGFcQoPBx22AAAEyKkQAAAEyKEAAAgEkRAgAAMClCAAAAJkUIAADApAgBAACYFCEAAACTIgQAt1lkZKT8/Pzk5+dncx/34m7FihXG53LEzV6u3NeKFSscUGHhad++vVH77Nmzi7oc4IZx22DgBvzyyy/q379/nu0uLi4qV66c7rrrLjVv3lz9+vWTt7d3EVToWCtWrNArr7xivHbkg2ZuxZUhY9q0aXrkkUeKsBrgzkEIAOyQnZ2ttLQ07dmzR3v27NGKFSu0ZMkS3XvvvUafsLAw43HHNWvWLKpSHS4gIEBjx4512P6u3BcPaAIKByEAuAVhYWFq3LixLl++rB07duj777+XJGVkZOi9997TvHnzjL4hISF5HkR0J6hfv74Rbhxh0KBBDtsXgBtDCABuwQMPPGAzJN21a1ft3btXkhQfH2/TNzIyUl9//bUkqWXLlvr4449t2k+cOKHFixdr06ZNOnLkiLKyslS1alU1a9ZM/fv3txlVkKTExEQtWbJEf/31l5KSkpScnKysrCxVqlRJ99xzj/r06aP27dvnW/eOHTv02WefacuWLTp58qRcXFxUrVo1NWvWTEOHDpWLi4s6dOiQ531XDsdHRERoxIgR+U4ZZGdnq0OHDjp69KhN3yu9/fbb+uCDDyRJ9erV03fffZfnGLlD/v369dOvv/5q8/5XXnnFOO5dd92lxYsXq1OnTsrOzpYkLVy4UG3atLF5z6OPPqqdO3dKkvr27avJkyfn+/O52s8//6wvvvhCf/zxh06dOiVXV1fVrFlTzZs318iRI20etpOfrKwszZkzR3/99ZcSEhJ07tw5ZWRkqEKFCvL19VVoaKj69u1r88hfSdqyZYsWLVqkHTt26OzZsypVqpQqVaokHx8fNWnSRAMHDlTFihUlSenp6frwww+1bt06HTx4UJmZmXJzc1O1atUUEBCghx9++I4MoXAMQgBgh8uXL+vPP/80TnqS8jw97Vp+++03DR8+XMnJyTbbk5KSlJSUpOjoaI0dO1ZPP/200bZ//34tWbIkz75OnjypkydPasOGDRoxYoQiIiJs2ufMmaM5c+bo6meGHTx4UAcPHlSHDh3UsGHDG649Py4uLurRo4cxErJq1SqbEGC1WhUTE2O8dsTcfp06dRQSEqIff/xRkrR8+XKbEJCYmGgEACknEFyP1WrVxIkTtXz5cpvtmZmZ2rdvn/bt26fHHnvsuiHg4sWLmj9/fp7t586d09atW7V161atX79eH3zwgUqUKCFJiouL06BBg3T58mWj/6VLl5Senq6kpCT99NNPCgsLM0LAc889lyconTlzRmfOnNHff/+t8+fPEwJQIEIAcAuu/G30Si4uLjc8rJ2SkqKIiAgjAJQpU0aPPPKIKlSooOjoaCUlJSk7O1tvvvmm7rnnHuMxyiVKlFCjRo3UuHFjeXp6qkKFCkpPT9fvv/+uX375RZI0f/589e7d23j2++rVq21WrZctW1ZhYWGqVauWkpKStH79ekmSh4eHxo4dq507d9qcrK+crw8MDLzm53rkkUc0f/58Wa1WHTx4UDt37lTjxo0lSVu3bjUCU4kSJWwebZufxx9/XA8++KDeeustY1vuVIwk40T41FNPGSFg3bp1OnPmjHGCXrNmjfHe+vXr5xlZyc/ChQttAoCHh4dCQ0NVpUoVJSQkGD+v67FYLPLy8lKTJk1UvXp1ubu769KlS0pISNCaNWuUlZWln3/+Wd99953CwsIkSZ9//rkRAHx8fNS5c2eVKFFCx44d0+7du7Vr1y5j/wcOHDACQG4Aq1evns6ePasjR47kCQfA1QgBgAONGjVKDz744A31XbFihc6dO2e8njVrltq2bStJGjhwoDp27Kj09HRZrVYtXrzYCAG5awwSEhK0e/dunTlzRiVLllTbtm21Y8cOZWRkKCsrS3FxccZJNioqyjhOuXLltGLFCpurGNLT041h6kGDBmnFihU2IeBm5uu9vLzUokUL4wQUHR1tnLSjo6ONfq1btzZCSkFyT4xXhoCrp2IkqU2bNqpXr54OHjyoS5cu6ZtvvjFGT1avXm30u5FRgOzsbC1cuNB4Xb16dX399deqXLmyse3s2bMqWfL6/3yWK1dOP/zwg06fPq3t27frxIkTunDhgvz9/bV3715jCmnTpk3GZ7148aLx/oiICIWHh9vs859//lGFChXy9PX29tbUqVNlsViMbZcvX9bx48evWyfMixAA3IIrFwbu379f0dHRysrK0r///W9dunQpz1B8frZv32782dPT0wgAklS5cmWFhIQYv8Ve2ffIkSMaM2aMtm3bds39nzhxQlLOYsUrf3vs3r17nssYy5Urp3Llyl235hv16KOPGiEgJiZGY8eO1eXLl21+K3fkZX4Wi0VPPfWUpkyZIilnSuDpp59WYmKi/vrrL0lSqVKl1K1bt+vuKyEhQWfOnDFe9+vXzyYASFKlSpVuqK4LFy5o8uTJWrlypbFmIT+5f1eS1Lx5c2OkITIyUsuWLZO3t7e8vb3VrFkz3XvvvcaJ3tfXVx4eHjp37pwOHDighx56SP7+/qpXr578/PwUHBysu+6664ZqhTkRAoBbcPVvo15eXpozZ46kvEPxBblyHUCVKlXytF+5LSUlxfjz8OHD9ffff1+3xszMTOO9V64DqF279nXfa69OnTrp9ddf1/nz53X8+HH99ttvunDhgnFy9fDwyHcBoj169uypmTNn6vz58zpw4IAx556rbdu2eU7m+blydEay7+c1Y8aMG7rxUe7flSQNGDBAe/bs0apVq5SZmalff/3VZli/QYMGWrhwoapVq6bSpUvr3Xff1fjx43X06FElJiYqMTHR6FuqVCm99NJLNmtKgCtxx0DAAa6cZ87KytKff/553fe4u7sbfz516lSe9iu3ubm5Scq58uDKANClSxdt3LhRf//9t/bs2ZPvQjU3NzebIeIjR45ctzZ75a45yLVq1SqbqYCuXbvK1dXVocesUKGCTTD78ssvb2nkwcPDw+a1PT+vK6ciGjRooFWrVumvv/7Snj171Llz53zfU7JkSb311lvatGmT5s6dqzFjxujRRx81/v+yd+9ezZgxw+gfHBysdevW6csvv9SUKVM0ePBgNW/eXFLOgsK33npLhw4duuXPgDsbIQBwgKtP+leu7C7IlQvszpw5o9jYWOP16dOntXHjxjx9r/4ttXPnzqpevbosFot++eUXm2HsXGXLlpW/v7/x+ptvvslzUrhw4YJOnz5tvL56vjsjI+O6n+dqV86/f/fdd/rhhx/ybbsRV9ZzrVqefPJJI/DknnClnFGVK6dbrsXb29smTH3yySd5fq7JyclKS0u77r6u/PsKCgpS/fr1VbJkSZ05c6bARXvx8fHKyMiQp6enOnbsqMGDB2vq1KkaNmyY0Sd3eufixYs6cOCAXFxcFBAQoN69e2vMmDH65JNPjEWT2dnZNzRyBHNiOgC4BT/99JPOnj2ry5cv68CBA1q1apXRVqJECTVp0uS6++jZs6fmzZtnnChGjhypRx99VBUqVNCqVauUnp4uKWe+e8CAAZKkunXrysXFxZhf/te//qXdu3fr3Llz1xx2Hjx4sEaNGiUpZxFgjx49jKsDjh8/rg0bNui1115Tx44dJSnPVMZLL72kwMBAubi4qHv37vlOX1wtMDBQPj4+io+PtzkZNmrUSI0aNbru+69UvXp1JSUlSZIWLVqkc+fOqUyZMvL391dwcLDRz9vbW61bt9amTZtshti7det2Qwv5pP+7wuPtt9+WJB0/flxhYWEKDQ1V5cqVlZSUpB9++EFLliy57ufw9vY2Fv8tX75cLi4uKlu2rL755pt8A5skLV68WP/973/VqlUr1a5dW1WqVFFycrJWrlxp9Mk9waekpBh3pAwICFC1atVUpkwZbd26VampqUb/3JEk4GqEAOAWxMTE2Kyev9KwYcNUo0aN6+7Dzc1Nc+bM0bBhw5SSkqILFy7o008/tenj4uKil19+2bgyoHLlyurTp4+WLVsmSTp27Jjmzp0rKWdYOD4+3maRWa7Q0FAdOHDAuE9Aenq6vvzyywJrCwwMVNWqVfXPP/9Iyrnsbt26dZJybnh0IyFAyhmCf+edd2y23ewogCQ99NBDWrx4saSc6/5nzZolKec3/ytDgJSzkG/Tpk12HXPQoEE6ePCgcZng2bNntXTp0puu+/nnn9eLL74oKWe05aOPPpKUcy+J1q1ba/Pmzfm+LyMjQxs2bMi3zcXFRc8884zNttx7F+Tn3nvvVYsWLW66dpgDIQCwk6urq6pWrarGjRurd+/eeuCBB274vS1atNCqVau0ePFi/fTTTzZ3DLzvvvvUr1+/PKMKEydOVLVq1fTVV1/p5MmTqlq1qkJDQzVy5EibefirRUREKCQkREuXLrW5Y2CVKlXUrFkzm1sAu7q6KioqSu+88462b99+Q0Pf+enevbtmzpxpTI+UKlVKXbp0uen9jB49WtnZ2Vq7dq3++eefa063tG3bVnXr1jWmPJo0aaK77777po5nsVg0ZcoUhYaG2twxsFSpUqpevbpatmx53YWfkhQeHi4XFxe99957OnDggMqXL6/7779fL7/8shFkrtarVy+5ublp+/btOnLkiM6cOaPs7GxVqVJFTZo0Ub9+/Yw5f3d3d02aNEm///67/v77b506dUqpqakqW7as6tWrpw4dOmjAgAE3PAoC87FYr759GAAUc4MGDTJGAyZPnqy+ffsWcUWAcyIeArgjHDhwQCdPntT27duNYXY3Nzd17dq1iCsDnBchAMAdISoqynhQU65Ro0apfPnyRVQR4PwIAQDuKK6urqpbt64GDBig3r17F3U5gFNjTQAAACbFzYIAADApQgAAACZFCAAAwKQIAQAAmBQhAAAAkyIEAABgUoQAAABMihAAAIBJEQIAADCp/w/70ksV2O1BhwAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Scatter plot of MWolecular Weight versus LogP**\n",
        "It can be seen that the 2 bioactivity classes are spanning similar chemical spaces as evident by the scatter plot of MW vs LogP."
      ],
      "metadata": {
        "id": "b3yyaXkrAcsL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(5.5,5.5))\n",
        "#sns.scatterplot(x='MW', y='LogP', data=df_2class, hue='bioactivity_class', size='pIC50', edgecolor='black', alpha=0.7)\n",
        "\n",
        "sns.scatterplot(x='MW', y= 'LogP', data = df_2class, hue= 'bioactivity_class', size= 'pIC50', edgecolor= 'black', alpha = 0.7)\n",
        "\n",
        "plt.xlabel('Molecular weight', fontsize= 14, fontweight= 'bold')\n",
        "plt.ylabel('LogP', fontsize= 14, fontweight= 'bold')\n",
        "plt.legend(bbox_to_anchor=(1.05,1), loc=2, borderaxespad=0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 530
        },
        "id": "-Qog9AYSAs8w",
        "outputId": "445ed55f-b0c4-4ad5-8161-c5af0ab8666a"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7d07e1910a90>"
            ]
          },
          "metadata": {},
          "execution_count": 36
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x550 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Box Plot pIC50 value**"
      ],
      "metadata": {
        "id": "kjAUi_MC9k0j"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(5.5,5.5))\n",
        "\n",
        "sns.boxplot(x= 'bioactivity_class', y= 'pIC50', data= df_2class)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize= 14, fontweight= 'bold')\n",
        "plt.xlabel('Bioactivity class', fontsize= 14, fontweight= 'bold')\n",
        "\n",
        "plt.savefig('plot_IC50.pdf')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "id": "xaVQLCiy7VQF",
        "outputId": "6a09a5c6-622b-4a15-802b-2cfd41455944"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x550 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PsOqKyysCZCv"
      },
      "source": [
        "**Statistical analysis | Mann-Whitney U Test**\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def mannwhitney(descriptor, verbose=False):\n",
        "  # https://machinelearningmastery.com/nonparametric-statistical-significance-tests-in-python/\n",
        "  from numpy.random import seed\n",
        "  from numpy.random import randn\n",
        "  from scipy.stats import mannwhitneyu\n",
        "\n",
        "# seed the random number generator\n",
        "  seed(1)\n",
        "\n",
        "# actives and inactives\n",
        "  selection = [descriptor, 'bioactivity_class']\n",
        "  df = df_2class[selection]\n",
        "  active = df[df.bioactivity_class == 'active']\n",
        "  active = active[descriptor]\n",
        "\n",
        "  selection = [descriptor, 'bioactivity_class']\n",
        "  df = df_2class[selection]\n",
        "  inactive = df[df.bioactivity_class == 'inactive']\n",
        "  inactive = inactive[descriptor]\n",
        "\n",
        "# compare samples\n",
        "  stat, p = mannwhitneyu(active, inactive)\n",
        "  #print('Statistics=%.3f, p=%.3f' % (stat, p))\n",
        "\n",
        "# interpret\n",
        "  alpha = 0.05\n",
        "  if p > alpha:\n",
        "    interpretation = 'Same distribution (fail to reject H0)'\n",
        "  else:\n",
        "    interpretation = 'Different distribution (reject H0)'\n",
        "\n",
        "  results = pd.DataFrame({'Descriptor':descriptor,\n",
        "                          'Statistics':stat,\n",
        "                          'p':p,\n",
        "                          'alpha':alpha,\n",
        "                          'Interpretation':interpretation}, index=[0])\n",
        "  filename = 'mannwhitneyu_' + descriptor + '.csv'\n",
        "  results.to_csv(filename)\n",
        "  return results"
      ],
      "metadata": {
        "id": "dSTZnmy797am"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mannwhitney('pIC50')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "SigdYoVz-nQl",
        "outputId": "6a9de46b-0334-44f5-99fb-86ccaa287db2"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Descriptor  Statistics         p  alpha                      Interpretation\n",
              "0      pIC50       761.0  0.000246   0.05  Different distribution (reject H0)"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-83c218cf-8bc5-42c7-a622-4e202b6adb56\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
              "      <th>p</th>\n",
              "      <th>alpha</th>\n",
              "      <th>Interpretation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>pIC50</td>\n",
              "      <td>761.0</td>\n",
              "      <td>0.000246</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Different distribution (reject H0)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-83c218cf-8bc5-42c7-a622-4e202b6adb56')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-83c218cf-8bc5-42c7-a622-4e202b6adb56 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-83c218cf-8bc5-42c7-a622-4e202b6adb56');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(5.5,5.5))\n",
        "\n",
        "sns.boxplot(x= 'bioactivity_class', y= 'MW', data= df_2class)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('MW', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_MW.pdf')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        },
        "id": "UActQ5ZK_CCE",
        "outputId": "4da91bef-9a17-445c-a240-fd96460562ce"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x550 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mannwhitney('MW')"
      ],
      "metadata": {
        "id": "EYM7gubtA7WH",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "outputId": "4b9c4792-ed22-43a0-bc1c-70d429e8b1c6"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Descriptor  Statistics         p  alpha  \\\n",
              "0         MW       356.0  0.761099   0.05   \n",
              "\n",
              "                          Interpretation  \n",
              "0  Same distribution (fail to reject H0)  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-17d681f5-8d7e-4d5c-a0ef-fd283d9d9860\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
              "      <th>p</th>\n",
              "      <th>alpha</th>\n",
              "      <th>Interpretation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>MW</td>\n",
              "      <td>356.0</td>\n",
              "      <td>0.761099</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Same distribution (fail to reject H0)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-17d681f5-8d7e-4d5c-a0ef-fd283d9d9860')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-17d681f5-8d7e-4d5c-a0ef-fd283d9d9860 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-17d681f5-8d7e-4d5c-a0ef-fd283d9d9860');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z5hyBhGqyc6J"
      },
      "source": [
        "#### **LogP**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "liEtkpI4yX9t",
        "outputId": "511f6766-d4d3-45d6-9980-f386a618ab79",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        }
      },
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.boxplot(x = 'bioactivity_class', y = 'LogP', data = df_2class)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('LogP', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_LogP.pdf')"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x550 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2KgV5v_oFLXh"
      },
      "source": [
        "**Statistical analysis | Mann-Whitney U Test**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B61UsGMIFLuE",
        "outputId": "787da452-1219-4dc2-e43b-442e6a156eac",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        }
      },
      "source": [
        "mannwhitney('LogP')"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Descriptor  Statistics         p  alpha  \\\n",
              "0       LogP       330.0  0.576137   0.05   \n",
              "\n",
              "                          Interpretation  \n",
              "0  Same distribution (fail to reject H0)  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e6b13aa7-6b0a-4e8a-a2fb-060145958b79\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
              "      <th>p</th>\n",
              "      <th>alpha</th>\n",
              "      <th>Interpretation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>LogP</td>\n",
              "      <td>330.0</td>\n",
              "      <td>0.576137</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Same distribution (fail to reject H0)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e6b13aa7-6b0a-4e8a-a2fb-060145958b79')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-e6b13aa7-6b0a-4e8a-a2fb-060145958b79 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-e6b13aa7-6b0a-4e8a-a2fb-060145958b79');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4db7LZLRym2k"
      },
      "source": [
        "#### **NumHDonors**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iru1JPM1yg5A",
        "outputId": "3b92e937-4c32-4ce7-fff9-15931f502de4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        }
      },
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.boxplot(x = 'bioactivity_class', y = 'NumHDonors', data = df_2class)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('NumHDonors', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_NumHDonors.pdf')"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x550 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vM5vZWanFe3c"
      },
      "source": [
        "**Statistical analysis | Mann-Whitney U Test**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mS-rOqq7Fd1E",
        "outputId": "45458be4-8e97-48e3-de55-a49c84da454f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        }
      },
      "source": [
        "mannwhitney('NumHDonors')"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Descriptor  Statistics         p  alpha  \\\n",
              "0  NumHDonors       411.0  0.817534   0.05   \n",
              "\n",
              "                          Interpretation  \n",
              "0  Same distribution (fail to reject H0)  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8b990b48-f1e3-438f-a62f-d19e38cafdd2\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
              "      <th>p</th>\n",
              "      <th>alpha</th>\n",
              "      <th>Interpretation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>NumHDonors</td>\n",
              "      <td>411.0</td>\n",
              "      <td>0.817534</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Same distribution (fail to reject H0)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8b990b48-f1e3-438f-a62f-d19e38cafdd2')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-8b990b48-f1e3-438f-a62f-d19e38cafdd2 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-8b990b48-f1e3-438f-a62f-d19e38cafdd2');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yOYQ3QiSyu7-"
      },
      "source": [
        "#### **NumHAcceptors**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yCw6tgNCyxHf",
        "outputId": "842ffe5a-2f9e-4fdb-93b9-1414e187941d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 513
        }
      },
      "source": [
        "plt.figure(figsize=(5.5, 5.5))\n",
        "\n",
        "sns.boxplot(x = 'bioactivity_class', y = 'NumHAcceptors', data = df_2class)\n",
        "\n",
        "plt.xlabel('Bioactivity class', fontsize=14, fontweight='bold')\n",
        "plt.ylabel('NumHAcceptors', fontsize=14, fontweight='bold')\n",
        "\n",
        "plt.savefig('plot_NumHAcceptors.pdf')"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 550x550 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NEQoDZctFtGG",
        "outputId": "142cf7d8-b7be-49dd-8b3d-11ce756d8f12",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        }
      },
      "source": [
        "mannwhitney('NumHAcceptors')"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Descriptor  Statistics         p  alpha  \\\n",
              "0  NumHAcceptors       383.0  0.968251   0.05   \n",
              "\n",
              "                          Interpretation  \n",
              "0  Same distribution (fail to reject H0)  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4f9e0901-aff9-4e7c-831c-08787d3b8a15\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Descriptor</th>\n",
              "      <th>Statistics</th>\n",
              "      <th>p</th>\n",
              "      <th>alpha</th>\n",
              "      <th>Interpretation</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>NumHAcceptors</td>\n",
              "      <td>383.0</td>\n",
              "      <td>0.968251</td>\n",
              "      <td>0.05</td>\n",
              "      <td>Same distribution (fail to reject H0)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4f9e0901-aff9-4e7c-831c-08787d3b8a15')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-4f9e0901-aff9-4e7c-831c-08787d3b8a15 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-4f9e0901-aff9-4e7c-831c-08787d3b8a15');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p4QjdHVjKYum"
      },
      "source": [
        "#### **Interpretation of Statistical Results**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mSoOBIqfLbDs"
      },
      "source": [
        "##### **Box Plots**\n",
        "\n",
        "###### **pIC50 values**\n",
        "\n",
        "Taking a look at pIC50 values, the **actives** and **inactives** displayed ***statistically significant difference***, which is to be expected since threshold values (``IC50 < 1,000 nM = Actives while IC50 > 10,000 nM = Inactives``, corresponding to ``pIC50 > 6 = Actives and pIC50 < 5 = Inactives``) were used to define actives and inactives.\n",
        "\n",
        "###### **Lipinski's descriptors**\n",
        "\n",
        "All the 4 Lipinski's descriptors (MW, LogP, NumHDonors and NumHAcceptors) shows ***statistically significant difference*** between **actives** and **inactives**."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U-rK8l0wWnKK"
      },
      "source": [
        "## **Zip files**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GW1ZSsfJWqbM",
        "outputId": "24032af7-64f9-4269-f7e8-c2eb7fa818ae",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "! zip -r results.zip . -i *.csv *.pdf"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "  adding: plot_LogP.pdf (deflated 38%)\n",
            "  adding: mannwhitneyu_pIC50.csv (deflated 11%)\n",
            "  adding: bioactivity_data_preprocessed.csv (deflated 82%)\n",
            "  adding: plot_biactivity_class.pdf (deflated 37%)\n",
            "  adding: plot_NumHAcceptors.pdf (deflated 38%)\n",
            "  adding: plot_IC50.pdf (deflated 38%)\n",
            "  adding: plot_NumHDonors.pdf (deflated 37%)\n",
            "  adding: mannwhitneyu_LogP.csv (deflated 7%)\n",
            "  adding: mannwhitneyu_NumHAcceptors.csv (deflated 10%)\n",
            "  adding: mannwhitneyu_MW.csv (deflated 8%)\n",
            "  adding: bioactivity_data_raw.csv (deflated 90%)\n",
            "  adding: mannwhitneyu_NumHDonors.csv (deflated 10%)\n",
            "  adding: plot_MW.pdf (deflated 38%)\n"
          ]
        }
      ]
    }
  ]
}