bio-structural-biology-modern-structure-prediction
Predict protein structures using modern ML models including AlphaFold3, ESMFold, Chai-1, and Boltz-1. Use when predicting structures for novel proteins, protein complexes, or when comparing predictions across multiple methods.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-structural-biology-modern-structure-prediction --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.
## Version Compatibility Reference examples tested with: BioPython 1.83+, numpy 1.26+ Before using code patterns, verify installed versions match. If versions differ: - Python: `pip show <package>` then `help(module.function)` to check signatures - CLI: `<tool> --version` then `<tool> --help` to confirm flags If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Modern Structure Prediction **"Predict the structure of my protein"** → Run ML-based structure prediction using ESMFold (single-sequence, fast), AlphaFold3 (MSA-based, highest accuracy), Chai-1, or Boltz-1 and compare predictions across methods. - Python: ESMFold API via `requests`, local ESMFold with `esm.pretrained` Predict protein structures using state-of-the-art machine learning models. This covers cloud APIs, local installations, and interpretation of results. ## Model Comparison | Model | Complexes | Ligands | Speed | Access | |-------|-----------|---------|-------|--------| | AlphaFold3 | Yes | Yes | Slow | Server only (2025) | | ESMFold | No | No | Fast | API or local | | Chai-1 | Yes | Yes | Moderate | Local
- Version Compatibility
- Model Comparison
- ESMFold (Fastest Single-Chain)
- Via ESM Atlas API
- Local ESMFold
- AlphaFold3 (Server)
- Prepare Input JSON
- Process AF3 Results
- AF3 Confidence Interpretation
- Chai-1 (Local Open-Source)
- Installation
- Basic Prediction
- Chai-1 with Ligands
- Boltz-1 (Open-Source Complex Prediction)
pip install chai-lab pip install boltz Install ColabFold pip install colabfold Run prediction colabfold_batch input.fasta output_dir/ With custom templates colabfold_batch input.fasta output_dir/ --templates For complexes (use : to separate chains) Create FASTA like: >complex\nSEQUENCE1:SEQUENCE2
What does the bio-structural-biology-modern-structure-prediction skill do?
Predict protein structures using modern ML models including AlphaFold3, ESMFold, Chai-1, and Boltz-1. Use when predicting structures for novel proteins, protein complexes, or when comparing predictions across multiple methods.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill bio-structural-biology-modern-structure-prediction --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.