method-geometric-learning

SchNetPack - Deep Neural Networks for Atomistic Systems

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

OpenFF NAGL

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

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

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

A Euclidean diffusion model for structure-based drug design.

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.

A powerful and flexible machine learning platform for drug discovery

Python package for graph neural networks in chemistry and biology

Standalone charge assignment from Espaloma framework.

Message Passing Neural Networks for Molecule Property Prediction