Boltz
github.com/jwohlwend/boltzFirst fully open-source model achieving AlphaFold3-level accuracy with 1000x faster binding affinity prediction (MIT)
Sourced from
- Awesome AI for Science — github.com/jwohlwend/boltz
- GitHub — github.com/jwohlwend/boltz
Related resources
Deep learning library for Chemistry based on Tensorflow
Trainable, memory-efficient PyTorch reproduction and retraining of AlphaFold2 providing new insights into its learning dynamics and out-of-distribution generalization; widely used as the open-source AlphaFold2 backbone underpinning many downstream protein structure prediction and design pipelines (Columbia AlQuraishi Lab & OpenFold Consortium, Nature Methods 2024)
AlphaFold/ESMFold accessible implementation with AF3 JSON export, database updates
Directed message passing neural networks for property prediction of molecules and reactions with uncertainty and interpretation.
Powerful and flexible machine learning platform for drug discovery, providing comprehensive tools for molecular property prediction, generative models, knowledge graph reasoning, and reaction prediction with PyTorch backend (1.5K+ stars)
Fast and accurate protein structure search using a learned 3Di structural alphabet (VQ-VAE) that discretizes tertiary interactions into structural tokens, enabling protein-universe-scale structural alignment at sequence-search speeds (4-5 orders of magnitude faster than DALI/TM-align) and underpinning many AI4S tools such as SaProt, ESMAtlas search, and AFDB clustering pipelines (Steinegger Lab, Nature Biotechnology 2023)