exercises/01_getting_started.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Our first real exercise with rdkit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "RDKit WARNING: [10:18:07] Enabling RDKit 2019.09.3 jupyter extensions\n"
     ]
    }
   ],
   "source": [
    "from rdkit import Chem\n",
    "from rdkit.Chem.Draw import IPythonConsole"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = Chem.MolFromSmiles(\"C(=O)c1ccccc1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# almost same molecule\n",
    "m1 = Chem.MolFromSmiles(\"c1ccccc1C(=O)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# completely different molecule\n",
    "cdm = Chem.MolFromSmiles(\"c1ccccc1C(=O)CCC1CC1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "O=Cc1ccccc1 O=Cc1ccccc1\n",
      "C(=O)c1ccccc1 c1ccccc1C=O\n"
     ]
    }
   ],
   "source": [
    "# compare\n",
    "print(Chem.MolToSmiles(m), Chem.MolToSmiles(m1))\n",
    "# with\n",
    "print(Chem.MolToSmiles(m, canonical=False), Chem.MolToSmiles(m1, canonical=False))\n",
    "# Do you remeber from lectures what cononical means?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "     RDKit          2D\n",
      "\n",
      "  8  8  0  0  0  0  0  0  0  0999 V2000\n",
      "    3.0000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n",
      "    3.7500   -1.2990    0.0000 O   0  0  0  0  0  0  0  0  0  0  0  0\n",
      "    1.5000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n",
      "    0.7500   -1.2990    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   -0.7500   -1.2990    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   -1.5000    0.0000    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n",
      "   -0.7500    1.2990    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n",
      "    0.7500    1.2990    0.0000 C   0  0  0  0  0  0  0  0  0  0  0  0\n",
      "  1  2  2  0\n",
      "  1  3  1  0\n",
      "  3  4  2  0\n",
      "  4  5  1  0\n",
      "  5  6  2  0\n",
      "  6  7  1  0\n",
      "  7  8  2  0\n",
      "  8  3  1  0\n",
      "M  END\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(Chem.MolToMolBlock(m))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x25a6af3f1c0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# rdkit can show your molecule (since 2019 without any manually added methods)\n",
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x25a6af3f210>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looks almost the same, but different atom numbering\n",
    "m1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How to calculate all rings in drug bank?\n",
    "Firstly, how can we work with rings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((2, 7, 6, 5, 4, 3),)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ri=m.GetRingInfo()\n",
    "ri.AtomRings()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((0, 5, 4, 3, 2, 1),)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# can you see different ids of atoms in the ring?\n",
    "ri=m1.GetRingInfo()\n",
    "ri.AtomRings()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<rdkit.Chem.rdchem.Mol at 0x25a6af3f990>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# advanced molecule\n",
    "cdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 1, 2)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# SSSR = smallest set of smallest rings\n",
    "Chem.GetSSSR(m), Chem.GetSSSR(m1), Chem.GetSSSR(cdm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "suppl = Chem.SDMolSupplier('../data/drugbank.sdf')  # Default working directory is where the notebook is\n",
    "drugs = [m for m in suppl if not m == None]  # supplier sometimes returns None, you can see many errors below\n",
    "\n",
    "#drugs = []\n",
    "#for m in suppl:\n",
    "#    drug.append(m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We obtained so many drugs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7113"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(drugs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With SSSR algorithm, we can calculate all rings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "rings = [Chem.GetSSSR(drug) for drug in drugs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[6, 6, 4, 6, 1, 4, 5, 1, 12, 3]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rings[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(<rdkit.Chem.rdchem.Mol at 0x25a6af571c0>, 6),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af57210>, 6),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af57260>, 4),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af572b0>, 6),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af57300>, 1),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af57350>, 4),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af573a0>, 5),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af4c4e0>, 1),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af573f0>, 12),\n",
       " (<rdkit.Chem.rdchem.Mol at 0x25a6af57440>, 3)]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[(m,r) for m, r in zip(drugs, rings[:10])]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sum of all rings give us"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17547"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(rings)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Average per compound"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.4668916069169127"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(rings)/len(drugs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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