Boltz-1 (AlphaFold3)
An open-source version of AlphaFold3 developed by an MIT lab.
Boltz-1 and Boltz-1x are open-source deep learning models achieving AlphaFold3-level accuracy in predicting the 3D structures of biomolecular complexes. Incorporating innovations in model architecture, data processing, and confidence prediction, Boltz-1 democratizes access to state-of-the-art tools for modeling biomolecular interactions. Released under the MIT license, Boltz-1 empowers researchers with comprehensive training code, model weights, and datasets to accelerate discoveries in drug design and structural biology.
Estimated resource cost: 0.0024025
Categories: Structure Prediction & Folding
Tags: Co-Folding Conformation Generation Macrocyclic Nucleotides Protein Folding Proteins Protein–Ligand Docking Protein–Protein Docking Small Molecules
Key Capabilities
- Achieves AlphaFold3-level accuracy for predicting 3D biomolecular complex structures.
- Supports diverse biomolecular systems, including proteins, nucleic acids, and small molecules.
- Innovative algorithms for MSA pairing, pocket-conditioning, and unified cropping.
- Optimized confidence model for reliable biomolecular interaction predictions.
- Significant speed and computational efficiency improvements over comparable models.
- Extensive benchmark validation on CASP15 and curated test sets.
- Supports the newer Boltz-1x version of the model.
Runtime Statistics
| Metric | Value |
|---|---|
| runtime_mean | 324 |
| runtime_median | 177 |
| runtime_std | 491 |
| runtime_90th_percentile | 683 |
| runtime_max | 8209 |
Similar Tools
- Boltz-2 (AlphaFold3)
- Chai-1 (AlphaFold3)
- IntelliFold (AlphaFold3)
- OpenFold3 (AlphaFold3)
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Estimated Credits: 0.0024025
Invite-only, limited-time access. Please contact ztang@getantibody.com.
Invite-only, limited-time access. Please contact ztang@getantibody.com.