protein-structure
Analyzes protein 3D structures, performs homology modeling, interprets AlphaFold predictions, conducts molecular docking, and evaluates protein-ligand interactions; trigger when users ask about PDB files, folding, binding sites, or structural biology.
Best use case
protein-structure is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Analyzes protein 3D structures, performs homology modeling, interprets AlphaFold predictions, conducts molecular docking, and evaluates protein-ligand interactions; trigger when users ask about PDB files, folding, binding sites, or structural biology.
Teams using protein-structure should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/protein-structure/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How protein-structure Compares
| Feature / Agent | protein-structure | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Analyzes protein 3D structures, performs homology modeling, interprets AlphaFold predictions, conducts molecular docking, and evaluates protein-ligand interactions; trigger when users ask about PDB files, folding, binding sites, or structural biology.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
## When to Trigger Activate this skill when the user mentions: - Protein folding, AlphaFold, ESMFold, RoseTTAFold - PDB files, structural analysis, Ramachandran plots - Molecular docking, binding affinity, binding pockets - Homology modeling, threading, ab initio structure prediction - Protein-protein interactions (PPI), interface analysis - Structural alignment, RMSD, TM-score - Cryo-EM, X-ray crystallography data interpretation ## Step-by-Step Methodology 1. **Retrieve or predict structure** - Search PDB for experimental structures (by UniProt ID or gene name). If unavailable, use AlphaFold DB or run ESMFold. Check pLDDT confidence scores for predicted structures. 2. **Quality assessment** - For experimental structures: check resolution, R-free, and completeness. For predictions: evaluate pLDDT per-residue and PAE (predicted aligned error) matrices. 3. **Structural analysis** - Identify secondary structure elements (helices, sheets, loops). Compute solvent-accessible surface area. Map conserved residues and functional domains. 4. **Binding site identification** - Use fpocket, SiteMap, or DoGSiteScorer for pocket detection. Cross-reference with known ligand binding from PDBe or BindingDB. 5. **Molecular docking** - Recommend AutoDock Vina, GNINA, or Glide. Define grid box around binding site. Report binding energy (kcal/mol) and key interactions (H-bonds, hydrophobic, pi-stacking). 6. **Structural comparison** - Align structures using TM-align or FATCAT. Report RMSD and TM-score. Identify conformational changes between states. 7. **Visualization guidance** - Recommend PyMOL, ChimeraX, or Mol* for rendering. Specify coloring schemes (by chain, B-factor, electrostatics, or conservation). ## Key Databases and Tools - **PDB / PDBe** - Experimental protein structures - **AlphaFold DB** - AI-predicted structures for UniProt entries - **UniProt** - Protein sequences, domains, and annotations - **InterPro / Pfam** - Domain classification - **BindingDB / ChEMBL** - Binding affinity data - **RCSB PDB REST API** - Programmatic structure queries - **PDBe-KB** - Aggregated structural annotations ## Output Format - Report structures with PDB ID, resolution, method, and chain identifiers. - Binding energies in kcal/mol with interaction fingerprints. - Structural alignments with RMSD (in Angstroms) and TM-score. - Residue numbering must match the canonical UniProt sequence or PDB SEQRES. - Include PyMOL/ChimeraX commands for reproducing visualizations. ## Quality Checklist - [ ] Structure source and method (X-ray, cryo-EM, NMR, predicted) clearly stated - [ ] Resolution or confidence metric (pLDDT) reported - [ ] Binding site residues listed with chain and numbering - [ ] Docking results include top poses and interaction details - [ ] Limitations of predicted structures acknowledged where relevant - [ ] All PDB IDs verified as valid and current - [ ] Biological assembly vs. asymmetric unit distinguished
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