method-geometric-learning

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

A Euclidean diffusion model for structure-based drug design.

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

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

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

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

[NeurIPS2025 Spotlight 🔥 ] Official implementation of "UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection"

SchNetPack - Deep Neural Networks for Atomistic Systems

OpenFF NAGL

A powerful and flexible machine learning platform for drug discovery

Python package for graph neural networks in chemistry and biology

Message Passing Neural Networks for Molecule Property Prediction

Standalone charge assignment from Espaloma framework.