| name | boltz |
| description | Structure prediction using Boltz-1/Boltz-2, an open biomolecular structure predictor. Use this skill when: (1) Predicting protein complex structures, (2) Validating designed binders, (3) Need open-source alternative to AF2, (4) Predicting protein-ligand complexes, (5) Using local GPU resources.
For QC thresholds, use protein-qc. For AlphaFold2 prediction, use alphafold. For Chai prediction, use chai.
|
| license | MIT |
| category | design-tools |
| tags | ["structure-prediction","validation","open-source"] |
| source | https://github.com/adaptyvbio/protein-design-skills |
Boltz Structure Prediction
Prerequisites
| Requirement | Minimum | Recommended |
|---|
| Python | 3.10+ | 3.11 |
| CUDA | 12.0+ | 12.1+ |
| GPU VRAM | 24GB | 48GB (L40S) |
| RAM | 32GB | 64GB |
How to run
Option 1: Modal
cd biomodals
modal run modal_boltz.py \
--input-faa complex.fasta \
--out-dir predictions/
Option 2: Local
pip install boltz
boltz predict --fasta complex.fasta --output predictions/
Output format
predictions/
├── model_0.cif # Best model (CIF format)
├── confidence.json # pLDDT, pTM, ipTM
└── pae.npy
Comparison
| Feature | Boltz-1 | Boltz-2 | AF2-Multimer |
|---|
| MSA-free | Yes | Yes | No |
| Open source | Yes | Yes | Yes |
| Speed | Fast | 2x faster | Slower |
Typical performance
| Campaign | Time (L40S) | Cost (Modal) |
|---|
| 100 complexes | 30-45 min | ~$8 |
| 500 complexes | 2-3h | ~$35 |
Troubleshooting
| Error | Cause | Fix |
|---|
CUDA out of memory | Complex too large | Use --use_msa_server false |
KeyError: 'iptm' | Single chain | Ensure 2+ chains in FASTA |
FileNotFoundError: weights | Missing model | Run boltz download first |
Next: protein-qc for filtering and ranking.
