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.
By