method-deep-learning

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

A Euclidean diffusion model for structure-based drug design.

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

Toward High-Accuracy Open-Source Biomolecular Structure Prediction.

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

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

Code for running RFdiffusion

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)

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

Differentiable, Hardware Accelerated, Molecular Dynamics

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

Deep Site and Docking Pose (DSDP) is a blind docking strategy accelerated by GPUs, developed by Gao Group. For the site prediction part, several modifications are introduced to PUResNet program. The pose sampling part is similar as AutoDock Vina combined with a number of modifications.

A deep learning framework for molecular docking

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]