Interface for AutoDock, molecule parameterization
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Updated
Jul 10, 2026 - Python
Interface for AutoDock, molecule parameterization
Predict protein-ligand and catalytic pockets and perform molecular docking of a specific ligand to each predicted pocket.
Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
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
pythonic interface to virtual screening software
Python3 translation of AutoDockTools
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.
AutoDock for GPUs and other accelerators
GPU-accelerated protein-ligand docking with automated pocket detection, exploring through multi-pocket conditioning. Official Implementation of PocketVina
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