Welcome to the repository for our latest project on virtual screening of small molecules using Lipinski's Rule of Five. This project aims to develop a comprehensive pipeline for filtering large sets of molecules based on Lipinski's Rule, a well-established guideline for predicting the oral bioavailability of drug candidates. The workflow includes:
- Reading SMILES strings from input files
- Converting SMILES to RDKit molecules
- Applying Lipinski's Rule of Five
- Saving filtered molecules in CSV and SDF formats
This repository includes the complete source code, documentation, and example datasets to reproduce the results. We believe this tool will be valuable for researchers in the fields of drug discovery and computational chemistry.
Picture Courtesy: Chagas, C. M., Moss, S., & Alisaraie, L. (2018). Drug metabolites and their effects on the development of adverse reactions: Revisiting Lipinski’s Rule of Five. International Journal of Pharmaceutics, 549(1-2), 133-149.
This Python script performs virtual screening of small molecules based on Lipinski’s Rule of Five. Below are the key steps involved:
-
Importing Required Modules
- The script imports necessary modules like
csv,rdkit, and functions fromLipinskiandDescriptors.
- The script imports necessary modules like
-
Reading SMILES Strings
- The script reads a list of SMILES strings from a CSV file.
-
Converting SMILES to RDKit Molecules
- Converts SMILES strings to RDKit molecule objects using
Chem.MolFromSmiles().
- Converts SMILES strings to RDKit molecule objects using
-
Applying Lipinski's Rule of Five
- Filters molecules based on hydrogen bond donors, acceptors, molecular weight, and logP.
-
Saving Filtered Molecules to CSV
- Writes the filtered molecules to a CSV file using
Chem.MolToSmiles().
- Writes the filtered molecules to a CSV file using
-
Final Output
- Prints the number of molecules that passed the filter.
This Python script generates 3D structures of the filtered molecules and saves them in SDF format.
-
Importing OS Module
- Uses the
osmodule to handle file operations and create directories.
- Uses the
-
Creating Output Folder
- Creates a folder named
Screened_Molecules_3Dto store SDF files.
- Creates a folder named
-
Saving Molecules in SDF Format
- Converts molecules to SDF format using
Chem.MolToMolBlock().
- Converts molecules to SDF format using
-
Storing SDF Files
- Stores all filtered molecules in SDF format for future use.
For more details, please reach out:
- Email: rikgangulybioinfo@gmail.com
- Lab: Computational Biology Laboratory,
North-Eastern Hill University, Shillong, India
This project is licensed under the MIT License. The MIT License allows:
- Free usage, modification, and distribution for any purpose.
- The project is provided "as is," without warranty of any kind.
- You must retain the original copyright notice in any copies.
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