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

Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"

Code for running RFdiffusion

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

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

A Euclidean diffusion model for structure-based drug design.

Official Github for "PharmacoNet: deep learning-guided pharmacophore modeling for ultra-large-scale virtual screening" (Chemical Science)

Knowledge-Guided Diffusion Model for 3D Ligand-Pharmacophore Mapping

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

This package contains deep learning models and related scripts for RoseTTAFold

Training and inference code for ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design [ICLR 2025 oral]

Toward High-Accuracy Open-Source Biomolecular Structure Prediction.

[PNAS 2025] Code of "Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design".

Code for the DISCO model: General Multimodal Protein Design Enables DNA-Encoding of Chemistry

AlphaFold 3 inference pipeline.

Chai-1, SOTA model for biomolecular structure prediction

PhoreGen: Pharmacophore-Oriented 3D Molecular Generation towards Efficient Feature-Customized Drug Discovery https://www.nature.com/articles/s43588-025-00850-5

Prediction of ligand binding site

The official PyTorch implementation of PGMG: A Pharmacophore-Guided Deep Learning Approach for Bioactive Molecule Generation.