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Open-source alternatives to Alphafold
12 open-source projects similar to google-deepmind/alphafold, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Alphafold alternative.
- deepmind/alphafold
deepmind/alphafold
14,687View on GitHubAlphaFold is a deep learning biology framework and machine learning pipeline designed to predict the three-dimensional coordinates of proteins based on their amino acid sequences. It functions as a bioinformatics inference system for calculating protein folding patterns and estimating prediction confidence. The system includes a protein multimer predictor for determining the 3D structures of protein complexes, supporting both homomers and heteromers. It utilizes specialized model presets to handle these complex structural predictions. The framework covers biological database management for m
Python - google-deepmind/alphafold3
google-deepmind/alphafold3
7,613View on GitHubAlphaFold3 is a biomolecular structure prediction model and bioinformatics structural analysis tool. It uses a deep learning system to predict the three-dimensional shapes of proteins, DNA, RNA, and ligands. The system functions as a diffusion-based protein folding model that predicts the spatial coordinates of biomolecular atoms and interactions. It utilizes a GPU-accelerated inference pipeline to process genetic sequences and structural templates for molecular modeling. The project covers structural bioinformatics analysis and protein interaction modeling to determine the physical arrangem
Python - jwohlwend/boltz
jwohlwend/boltz
4,038View on GitHubBoltz is a deep learning molecular modeler and biomolecular structure prediction system. It uses neural network architectures to simulate the physical folding and docking of biomolecules, specifically predicting the three-dimensional shapes of protein and ligand complexes. The project functions as a protein-ligand complex predictor and binding affinity predictor, estimating the strength and probability of molecular interactions between ligands and targets. These capabilities are applied to computer aided drug design, including ligand binding affinity prediction and protein-ligand interaction
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