boltzgen

name	boltzgen
description	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 backbone-only generation, use rfdiffusion. For sequence-only design, use proteinmpnn. For structure validation, use boltz.
license	MIT
category	design-tools
tags	["structure-design","sequence-design","diffusion","all-atom","binder"]
proteinbase_slug	boltzgen
proteinbase_url	https://proteinbase.com/design-methods/boltzgen
biomodals_script	modal_boltzgen.py

BoltzGen All-Atom Design

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

First time? See Installation Guide to set up Modal and biomodals.

Option 1: Modal (recommended)

# Clone biomodals
git clone https://github.com/hgbrian/biomodals && cd biomodals

# Run BoltzGen (requires YAML config file)
modal run modal_boltzgen.py \
  --input-yaml binder_config.yaml \
  --protocol protein-anything \
  --num-designs 50

# With custom GPU
GPU=L40S modal run modal_boltzgen.py \
  --input-yaml binder_config.yaml \
  --protocol protein-anything \
  --num-designs 100

GPU: L40S (48GB) recommended | Timeout: 120min default

Available protocols: protein-anything, peptide-anything, protein-small_molecule, nanobody-anything, antibody-anything

Option 2: Local installation

git clone https://github.com/HannesStark/boltzgen.git
cd boltzgen
pip install -e .

python sample.py config=config.yaml

Option 3: Python API

from boltzgen import BoltzGen

model = BoltzGen.load_pretrained()
designs = model.sample(
    target_pdb="target.pdb",
    num_samples=50,
    binder_length=80
)

GPU: L40S (48GB) | Time: ~30-60s per design

Key parameters (CLI)

Parameter