Welcome to this comprehensive hub of tools and resources for Computational Chemistry, with a special emphasis on drug design. This repository serves as a one-stop destination for computational chemists, researchers, and students seeking Python-based tools and pipelines for computer aided drug design.

This repository is dedicated to providing a suite of tools, scripts, and educational resources focused on advancing the field of Computational Chemistry. Here, you'll find a range of applications from molecular dynamics simulations to drug discovery methodologies, all aimed at supporting and enhancing research in this exciting domain.

Below is a summary of the key tools and resources available in this hub:

• Molecular Dynamics Simulations:

  • Tools and fully automated scripts for running MD simulations using major MD packages such as GROMACS,OpenMM and NAMD.
  • Tutorials and guides for setting up and analyzing simulations.

• Drug Design Techniques:

  • Python-based scripts for ligand docking, virtual screening, pharmacophore modeling, QSAR and Machine Learning models in various stages of drug design such as :
    • Hit to lead screening
    • Lead optimization
    • ADMET or DMPK prediction
  • Resources on structure-based and ligand-based drug design.

• Cheminformatics:

  • Utilities for molecular descriptor calculations, compound library management, and data analysis.
  • Integration of cheminformatics tools with machine learning models.

• Python Scripts for Computational Chemistry:

  • A collection of Python scripts to automate common tasks in computational chemistry workflows.
  • Customizable scripts for data processing, analysis, and visualization.

• Educational Materials and Tutorials:

  • Step-by-step guides for various computational chemistry techniques.
  • Learning resources for beginners and advanced users alike.

Contributions to this tool hub are welcome! Whether it's adding new tools, improving existing ones, or providing educational content, your input is valuable. Please see CONTRIBUTING.md for guidelines on how to contribute.

Feedback is crucial for the continuous improvement of this repository. If you have suggestions, questions, or comments, feel free to open an issue or submit a pull request.

This tool hub is open-source and available under the MIT License.

This project is made possible thanks to the contributions from the computational chemistry community and the use of various open-source software.

This hub is constantly evolving, with new tools and resources added regularly. Bookmark this repository and check back often for the latest in Computational Chemistry tools and techniques.

For more detailed information and documentation, visit my GitHub Pages site.