boltzgen

Generate side-chain-aware protein binder designs from YAML-configured campaigns using BoltzGen diffusion.

11|Updated Mar 4, 2026
One-click install
npx skills add https://github.com/junior1p/ProteinClaw --skill boltzgen-junior1p
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: boltzgen
Source: https://github.com/junior1p/ProteinClaw/tree/main/skills/boltzgen
Command: npx skills add https://github.com/junior1p/ProteinClaw --skill boltzgen-junior1p

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

BoltzGen removes the manual complexity of generating side-chain-aware protein binders by providing an all-atom diffusion workflow that produces geometry-precise designs from YAML specifications, enabling researchers to design binders against proteins, peptides, and small molecules with GPU-accelerated performance.

Core Features & Use Cases

  • All-atom diffusion: Generates designs with explicit side-chains for precise interface geometry.
  • YAML-driven campaigns: Entity-based YAML configuration for targets, restraints, and pipelines.
  • Multi-protocol support: Protocols for protein, peptide, nanobody, antibody, and protein–small molecule design.
  • Execution modes: Run via Modal for cloud GPU orchestration or local installation for on-prem GPUs.
  • Practical outputs & QC: Produces design.cif, sequence.fasta, and metrics.json for downstream validation and quality control.
  • Use case: Create 50 candidate binder designs for a receptor target and validate top candidates with downstream structure QC and scoring pipelines.

Quick Start

Design 50 side-chain-aware binders for target.cif using binder_config.yaml with the protein-anything protocol.

Frequently Asked Questions about boltzgen

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design side-chain-aware protein binders using all-atom diffusion?

To design side-chain-aware protein binders, you use an all-atom diffusion workflow that generates geometry-precise structures from YAML specifications. This produces explicit side-chains for accurate interface geometry across proteins, peptides, and small molecules.

What file formats do I need for target proteins in a YAML-driven binder generation campaign?

For a YAML-driven binder generation campaign, you need CIF or PDB files for your target proteins. The workflow uses entity-based YAML configuration to define targets and restraints, outputting design.cif and sequence.fasta files.

Does all-atom protein design require a CUDA-enabled GPU?

Yes, all-atom protein design requires a CUDA-enabled GPU for execution. You can run the diffusion workflow via Modal for cloud GPU orchestration or use a local installation for on-prem GPUs.

Can I generate nanobody and antibody designs with side-chain-aware diffusion?

Yes, you can generate nanobody and antibody designs using side-chain-aware diffusion. The system supports multi-protocol configurations for protein, peptide, nanobody, antibody, and protein-small molecule binding scenarios.

What outputs does an all-atom binder generation workflow produce for downstream validation?

An all-atom binder generation workflow produces design.cif, sequence.fasta, and metrics.json outputs. These files provide the generated structures, sequences, and quality control metrics needed for downstream structure validation and scoring.