All-atom protein design using BoltzGen diffusion model. Use this skill when: (1) Need side-chain aware design from the start, (2) Designing around small molecules or ligands, (3) Want all-atom diffusion (not just backbone), (4) Require precise binding geometries, (5) Using YAML-based configuration. For structure validation, use boltz-2.
| Requirement | Minimum | Recommended |
|---|---|---|
| Python | 3.10+ | 3.12 |
| CUDA | 12.0+ | 12.2 |
| GPU VRAM | 24GB | 80GB (A800) |
| RAM | 32GB | 64GB |
git clone https://github.com/HannesStark/boltzgen.git
cd boltzgen
pip install -e .
boltzgen run example/vanilla_protein/1g13prot.yaml \
--output workbench/test_run \
--protocol protein-anything \
--num_designs 10 \
--budget 2
# --num_designs is the number of intermediate designs. In practice you will want between 10,000 - 60,000
# --budget is how many designs should be in the final diversity optimized set
BoltzGen uses an entity-based YAML format to specify what to design and what the target is.
Important notes:
label_seq_id (1-indexed), not auth_seq_idboltzgen check config.yaml to verify before running