Predict protein-ligand and catalytic pockets and perform molecular docking of a specific ligand to each predicted pocket.

Interface for AutoDock, molecule parameterization

Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

AutoDock Vina

Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.

Open Drug Discovery Toolkit

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

Protein Ligand INteraction Dataset and Evaluation Resource

pythonic interface to virtual screening software

Python3 translation of AutoDockTools

AutoDock for GPUs and other accelerators

A deep learning framework for molecular docking

Deep Site and Docking Pose (DSDP) is a blind docking strategy accelerated by GPUs, developed by Gao Group. For the site prediction part, several modifications are introduced to PUResNet program. The pose sampling part is similar as AutoDock Vina combined with a number of modifications.

GPU-accelerated protein-ligand docking with automated pocket detection, exploring through multi-pocket conditioning. Official Implementation of PocketVina