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

🧬 gget enables efficient querying of genomic reference databases

Optimizing AlphaFold Training and Inference on GPU Clusters

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

User friendly and accurate binder design pipeline

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

Trainable AlphaFold implementation in JAX

Predicting direct protein-protein interactions with AlphaFold deep learning neural network models.

Modified version of Alphafold to divide CPU part (MSA and template searching) and GPU part. This can accelerate Alphafold when predicting multiple structures

PyMOL extension to color AlphaFold structures by confidence (pLDDT).

MMseqs2 app to run on your workstation or servers

Exploring Evolution-aware & free protein language models as protein function predictors

Protein 3D structure prediction pipeline

FrameDiPT: an SE(3) diffusion model for protein structure inpainting

Local Interaction Score (LIS) Calculation from AlphaFold-Multimer (Enhanced Protein-Protein Interaction Discovery via AlphaFold-Multimer)

Run AlphaFold2 (and multimer) step by step

A curated list of awesome self-learning materials in Computational Structural Biology, such as sources, tutorials, etc.

Infrastructure template and Jupyter notebooks for running RoseTTAFold on AWS Batch.

Cryptic pocket prediction using AlphaFold 2

A tool for predicting the effects of missense mutations on protein stability changes upon missense mutation using protein sequence only. PROST uses colab AlhpaFold2 for the prediction of pdb struture from FASTA sequence.