Official git repository for Biopython (originally converted from CVS)

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

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

Standardized data set for machine learning of protein structure

Working with molecular structures in pandas DataFrames

Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.

Protein-Ligand Interaction Profiler - Analyze and visualize non-covalent protein-ligand interactions in PDB files according to 📝 Schake, Bolz, et al. (2025), https://doi.org/10.1093/nar/gkaf361

Optimizing AlphaFold Training and Inference on GPU Clusters

Saprot: Protein Language Model with Structural Alphabet (AA+3Di)

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

An open-source platform for developing protein models beyond AlphaFold.

Protein-protein, protein-peptide and protein-DNA docking framework based on the GSO algorithm

An all-atom protein structure dataset for machine learning.

A Python API for the RCSB Protein Data Bank (PDB)

Recurrent Geometric Networks for end-to-end differentiable learning of protein structure

Versatile computational pipeline for processing protein structure data for deep learning applications.

Source code for "Learning protein sequence embeddings using information from structure" - ICLR 2019

Trainable PyTorch framework for developing protein, RNA and complex models.

Benchmarking framework for protein representation learning. Includes a large number of pre-training and downstream task datasets, models and training/task utilities. (ICLR 2024)

Deep generative models of 3D grids for structure-based drug discovery