OpenMM is a toolkit for molecular simulation using high performance GPU code.

Python implementation of the multistate Bennett acceptance ratio (MBAR)

Making Protein folding accessible to all!

ColabFold on your local PC

GPU-accelerated molecular docking software: Uni-Dock 2

An interoperable Python framework for biomolecular simulation.

Open Babel is a chemical toolbox designed to speak the many languages of chemical data.

Tools for preparation and analysis of systems for molecular dynamics.

Interfacing RDKit and AutoDock

Uni-Dock: a GPU-accelerated molecular docking program

Foundation Model for Materials - FM4M

EnzyDock: Protein–Ligand Docking of Multiple Reactive States along a Reaction Coordinate in Enzymes

Use AutoDock for Ligand-based Virtual Screening

IUPAC-based large-scale molecular pre-trained model for property prediction and molecular generation

active learning for accelerated high-throughput virtual screening

Open source documentation of Microsoft Azure

The official sources for the RDKit library

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecul…

DeepRMSD+Vina is a computational framework that integrates ligand binding pose optimization and screening.

P2Rank: Protein-ligand binding site prediction tool based on machine learning. Stand-alone command line program / Java library for predicting ligand binding pockets from protein structure.

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Official implementation of "Generating 3D Molecules for Target Protein Binding"

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.