Toolbox for molecular animations in Blender, powered by Geometry Nodes.

Sidechain conditioning and modeling for full-atom protein sequence design

Inference code for scalable emulation of protein equilibrium ensembles with generative deep learning

Learning the language of protein-protein interactions

Target Sequence-Conditioned Generation of Peptide Binders via Masked Language Modeling

Effectively addressing data bias to enhance peptide-protein interaction prediction via graph neural networks

Colab Notebooks covering deep learning tools for biomolecular structure prediction and design

A trainable PyTorch reproduction of AlphaFold 3.

PocketGen (Nature Machine Intelligence 24): Generating Full-Atom Ligand-Binding Protein Pockets

MCGLPPI and MCGLPPI++: Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction

AI-powered ab initio biomolecular dynamics simulation

Code and Pre-Trained Models for "AttnPacker: An end-to-end deep learning method for protein side-chain packing"

Chai-1, SOTA model for biomolecular structure prediction

predicting peptide-protein interactions

In silico directed evolution of peptide binders with AlphaFold

Public RFDiffusionAA repo

Ankh: Optimized Protein Language Model

Graph Network for protein-protein interface including language model features

Directed evolution of proteins in sequence space with gradients

Code for ProRefiner: An Entropy-based Refining Strategy for Inverse Protein Folding with Global Graph Attention

A generative model for programmable protein design

Code for ColabDock paper

Diffusion-based all-atom protein generative model.

The official implementation of the ICLR'23 paper PiFold: Toward effective and efficient protein inverse folding.