End-To-End Molecular Dynamics (MD) Engine using PyTorch

SchNetPack - Deep Neural Networks for Atomistic Systems

Extensible Surrogate Potential of Ab initio Learned and Optimized by Message-passing Algorithm 🍹https://arxiv.org/abs/2010.01196

Differentiable, Hardware Accelerated, Molecular Dynamics

Experiments with expanded ensembles to explore chemical space

Quantum chemistry program executor and IO standardizer (QCSchema).

NequIP is a code for building E(3)-equivariant interatomic potentials

Message Passing Neural Networks for Molecule Property Prediction

A deep learning package for many-body potential energy representation and molecular dynamics

Public/backup repository of the GROMACS molecular simulation toolkit. Please do not mine the metadata blindly; we use https://gitlab.com/gromacs/gromacs for code review and issue tracking.

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

MaSIF- Molecular surface interaction fingerprints. Geometric deep learning to decipher patterns in molecular surfaces.

Public development project of the LAMMPS MD software package

A powerful and flexible machine learning platform for drug discovery

Python package for graph neural networks in chemistry and biology

Foundation Models for Genomics & Transcriptomics

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

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

The Open Free Energy toolkit