bindcraft
End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bindcraft --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# BindCraft Binder Design ## Prerequisites | Requirement | Minimum | Recommended | |-------------|---------|-------------| | Python | 3.9+ | 3.10 | | CUDA | 11.7+ | 12.0+ | | GPU VRAM | 32GB | 48GB (L40S) | | RAM | 32GB | 64GB | ## How to run > **First time?** See [Installation Guide](../../docs/installation.md) to set up Modal and biomodals. ### Option 1: Modal (recommended) ```bash cd biomodals modal run modal_bindcraft.py \ --target-pdb target.pdb \ --target-chain A \ --binder-lengths 70-100 \ --hotspots "A45,A67,A89" \ --num-designs 50 ``` **GPU**: L40S (48GB) | **Timeout**: 3600s default ### Option 2: Local installation ```bash git clone https://github.com/martinpacesa/BindCraft.git cd BindCraft pip install -r requirements.txt python bindcraft.py \ --target target.pdb \ --target_chains A \ --binder_lengths 70-100 \ --hotspots A45,A67,A89 \ --num_designs 50 ``` ## Key parameters | Parameter | Default | Range | Description | |-----------|---------|-------|-------------| | `--target-pdb` | required | path | Target structure | | `--target-chain` | required | A-Z | Target chain(s) | | `--binder-lengths` | 70-100 | 40-150 | Length range | | `--hotspots` | None | residues | Target ho
- Prerequisites
- How to run
- Option 1: Modal (recommended)
- Option 2: Local installation
- Key parameters
- Protocols
- Output format
- Metrics Output
- Sample output
- Successful run
- Decision tree
- Typical performance
- Verify
- Troubleshooting
cd biomodals modal run modal_bindcraft.py \ git clone https://github.com/martinpacesa/BindCraft.git cd BindCraft pip install -r requirements.txt python bindcraft.py \ find output -name "binder.pdb" | wc -l # Should match num_designs
What does the bindcraft skill do?
End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bindcraft --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.