method-deep-learning

Toward High-Accuracy Open-Source Biomolecular Structure Prediction.

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

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

Comprehensive library for fast, GPU accelerated molecular gridding for deep learning workflows

Code for running RFdiffusion

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

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

Differentiable, Hardware Accelerated, Molecular Dynamics

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

A Euclidean diffusion model for structure-based drug design.

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

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

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

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]

Predicting protein-ligand binding sites using deep convolutional neural network

Reaction fingerprints, atlases and classification. Code complementing our Nature Machine Intelligence publication on "Mapping the space of chemical reactions using attention-based neural networks" (http://rdcu.be/cenmd).

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