AlphaFold2
SkillMonitoring & opsPredict the 3D structure of proteins, either single chains or complexes made of several chains, and check how confident each prediction is. Your AI can also audit existing protein structures and compare them against known references from the PDB and AlphaFold.
Available today. Use it from your connected AI after setup.
No other account needed.
Give your AI a protein sequence or a research task that involves protein structures and ask it to predict or audit them.
Then ask your AI: use the AlphaFold2 skill
What your AI can do with it
- Predict structures for single proteins and multi-chain complexes
- Check confidence metrics to see how reliable a prediction is
- Use sequence alignments and structural templates as part of the prediction
- Compare predicted structures against PDB and AlphaFold references
- Audit existing protein structures
What this skill tells your AI
The instructions your AI receives, as published by companion-inc/feynman in skills/alphafold2/SKILL.md and read by ahel’s review.
Use this skill for protein-structure prediction or parity checks around AlphaFold2-style outputs.
Workflow:
- Capture the biological question, sequence identifiers, FASTA input, oligomer state, organism, and expected cofactors or partners.
- Verify the execution route before running: local install, managed endpoint, Modal/SSH job, or a documented public source. Do not assume weights, databases, or GPUs exist.
- Save inputs, command or endpoint payload, model settings, stdout/stderr, and raw outputs under the active Feynman artifact folder.
- Report pLDDT, PAE, ranking confidence, chain coverage, truncation, templates/MSA provenance, and any residues or interfaces that should not be trusted.
- Compare against known structures or AlphaFold DB records when the claim depends on novelty, domain movement, interface geometry, or mutation impact.
Outputs should include the FASTA, predicted PDB/mmCIF, confidence files when available, a short method note, and a .provenance.md sidecar.
Signals
- GitHub stars
- 9k
- Forks
- 1k
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
alphafold2- Source
- github.com/companion-inc/feynman