boltz

Predict biomolecular structures with Boltz-1 and Boltz-2 on local GPUs.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Boltz Structure Prediction provides local, open-source protein structure prediction to accelerate design validation and reduce reliance on external services.

Core Features & Use Cases

  • Predict protein and complex structures with Boltz-1 and Boltz-2.
  • Validate designed binders and explore structural hypotheses on GPU-enabled hardware.
  • Use open-source, offline workflows as an alternative to cloud-based predictors.

Quick Start

Install Boltz and run boltz predict on your local FASTA file to generate structure predictions.

Frequently Asked Questions about boltz

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

FAQPage Schema
How do I run protein structure prediction locally on a GPU?▼

Run local protein structure prediction by executing the boltz predict command on a FASTA file. This requires a CUDA-enabled GPU (CUDA 12.x) and Python 3.10+ to generate CIF models, confidence.json, and pae.npy outputs.

Can I validate designed protein binders offline without cloud services?▼

Yes, you can validate designed protein binders offline using open-source, GPU-accelerated structure prediction. This local workflow serves as an alternative to cloud-based predictors, reducing reliance on external services.

What hardware do I need for biomolecular structure prediction with Boltz?▼

Biomolecular structure prediction with Boltz requires a local environment with CUDA-enabled GPUs (CUDA 12.x) and sufficient VRAM. You also need Python 3.10 or higher installed to execute the predictions.

What output files are generated when predicting protein complex structures?▼

Predicting protein complex structures generates CIF models, confidence.json, and pae.npy files. These outputs provide the structural coordinates and confidence metrics needed for analysis.

Is there an open-source alternative to cloud-based protein structure predictors?▼

Yes, Boltz offers an open-source alternative to cloud-based protein structure predictors. It runs locally on your hardware, using Boltz-1 and Boltz-2 models for offline biomolecular structure prediction.

Why does local structure prediction require significant VRAM?▼

Local structure prediction requires significant VRAM because the GPU-accelerated Boltz-1 and Boltz-2 models process complex biomolecular computations. Insufficient VRAM will prevent the local environment from running predictions effectively.