Further improved the README.md file.

README.md

@@ -1,49 +1,41 @@
 # MolecularDockingKit
 
-A simple python tool to perform molecular docking computations.
-
--------------------------------------- Outline of the program ---------------------------------------------
-Main script to run:
-  make.bash
-
-Supplementary scripts:
-  1) main.py
-  2) getSmilesFromFile.py
-  3) xyzFromSmiles.py
-  4) getScores.tcsh
-  5) call_combine.tcsh
-  6) combine.py
-  7) run.slurm inside a directory named energy_protein
-  8) getEnergy.py
-  9) run_template.slurm
-
-Files and directories needed from the user:
-  1) A file named "drugs.txt" which contains the initial data from the website given in the problem.
-  2) A file named "3sxr_dasatinib_removed.pdb" containing the protein without dasatinib. I could have
-     removed this user input but kept it this way.
-  3) A directory named "energy_protein" that contains a slurm script run.py which would submit the job
-     for protein.py such as run.slurm
-  4) A template file named 'prm-template.prm' for the prm input file to be used for docking calculations.
-
--------------------------------------- Summary of the program ---------------------------------------------
-All of the scripts contain comments to clarify their purpose in the program. A brief summary is provided below:
-1) The bash script main.bash calls main.py.
-   - main.py extracts the smiles formats for the drugs from the file called drugs.txt.
-   - A directory structure is created for the docking calculations which looks like:
-     |---- rDock_inputs/
-     |     |----MoleculeName/
-   - xyz coordinates are generated from the smiles using the script xyzFromSmiles
-   - .prm input files are generated from the prm-template.prm and are stored as moleculeName_rdock.prm as:
-     |---- rDock_inputs/
-     |     |----MoleculeName/
-     |     |    |----moleculeName_rdock.prm 
-2) A 10 runs-per-ligand rDock job is submitted for each drug molecule.
-3) getScores.tcsh is called to extract the scores from the docking output files.
-4) The scores and the molecule names are put in a file and molecule are sorted according to their docking scores. 
-5) A shell script call_combine is called which submits slurm jobs for binding energy calculations.
-6) Energy calculations are submitted for the protein without ligand.
-7) A python script getEnergy.py is called to extract energies and return binding energies in kcal/mol.
-8) Molecules are sorted according to their binding energies to get their ranking.
-__________________________________________________________________________________________________________
+MolecularDockingKit is a Python tool designed for molecular docking computations. It provides a simple and efficient way to perform docking simulations and analyze the results.
 
+## Overview
 
+The repository contains scripts and supplementary files necessary for running molecular docking simulations and analyzing the output data. Below is a brief overview of the main components:
+
+- **Main Script**: `make.bash`
+- **Supplementary Scripts**:
+  - `main.py`
+  - `getSmilesFromFile.py`
+  - `xyzFromSmiles.py`
+  - `getScores.tcsh`
+  - `call_combine.tcsh`
+  - `combine.py`
+  - `run.slurm` (inside the `energy_protein` directory)
+  - `getEnergy.py`
+  - `run_template.slurm`
+
+## Usage
+
+To use MolecularDockingKit, follow these steps:
+
+1. Prepare input files:
+   - Create a `drugs.txt` file containing initial data.
+   - Obtain a `3sxr_dasatinib_removed.pdb` file representing the protein without dasatinib.
+   - Set up a directory named `energy_protein` with a `run.py` script for submitting protein jobs.
+   - Provide a template file named `prm-template.prm` for the prm input file used in docking calculations.
+
+2. Execute the main script `make.bash` to initiate the docking computations.
+
+3. Follow the instructions provided in the comments of each script to understand their specific functions and requirements.
+
+## Contributing
+
+Contributions to MolecularDockingKit are welcome! If you encounter any issues or have suggestions for improvement, please feel free to open an issue or submit a pull request.
+
+## License
+
+This project is licensed under the [MIT License](LICENSE).