This is a repository where you can find Jupyter Notebook scripts for running Molecular Docking using Google Colab. This repository is created by Mostafa S. Abd El-Maksoud and I encourage you to read the instructions and watch the tutorials before using this pipeline. The main goal of this work is to demonstrate how to perform molecular docking using open-source software in a cheap yet feasible fashion 🚀.
Important
- Don't
Run all
cells at the beginning. Run the cells individually and wait for the session to restart. - This notebook is designed for
Google Colab
and may not work onother platforms
. - This notebooks provide a simple pipeline for illustrating Molecular Docking and
doesn't necessarily reflect the standard protocol
. - Don't forget to
save a copy from this notebook
in your drive before starting.
Introduction
- Molecular docking is a computational technique that predicts the preferred orientation of a molecule (such as a drug candidate) to a second molecule (such as a protein receptor) when they bind to form a stable complex. This method is extensively used in drug discovery and development to model the interaction between small molecules and their biological targets. It provides insights into potential drug compounds' binding affinity and activity.
Using Molecular Docking on Google Colab
- Google Colab provides access to free GPUs and TPUs, which can significantly speed up computations without needing expensive hardware.
- Being cloud-based, Colab eliminates the need for local installations and hardware maintenance.
- Users can easily install additional software and dependencies via simple terminal commands in Colab notebooks.
- Multiple users can work on the same notebook simultaneously, making collaborating on projects and sharing results easy.
- You can store input files and results directly in Google Drive, ensuring easy access and management.
- Sharing data and results with collaborators is straightforward using Google Drive.
- The workflows can be shared and rerun by others, ensuring the reproducibility of the computational experiments.
- Users can leverage Colab’s computational power to run multiple docking simulations in parallel, enhancing throughput and efficiency.
Use the appropriate software according to your methodology
- AutoDock Vina -
Using AutoDock vina software
- Virtual screening -
Using AutoDock Vina for multiple ligands docking
- AutoDock4.2 -
Using AutoGrid and AutoDock files inputs
Copyright (c) 2024 Mostafa S. Abd El-Maksoud