# Structural Biology

> Structural biology analysis including protein structure validation, AlphaFold interpretation, and structural comparisons

- Skill: `majiayu000/structural-biology` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/structural-biology`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/structural-biology/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/structural-biology

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# Structural Biology Analysis

## When to Use This Skill

- When analyzing protein or molecular structures
- When interpreting AlphaFold predictions
- When comparing experimental vs predicted structures
- When validating crystallographic or cryo-EM models

## Core Topics

This skill covers:

1. **AlphaFold Confidence Interpretation** - Understanding pLDDT scores and prediction reliability
2. **Structure Comparison** - Methods for comparing and aligning structures
3. **Validation Metrics** - Assessing model quality (R-factors, Ramachandran, clashscores)
4. **Interpreting Discrepancies** - Understanding differences between predicted and experimental structures

## Reference Files

For detailed guidance on specific topics, see:

- [alphafold-confidence.md](alphafold-confidence.md) - Interpreting AlphaFold confidence scores
- [comparing-structures.md](comparing-structures.md) - Structure alignment and comparison methods
- [validation-metrics.md](validation-metrics.md) - Quality metrics for structural models
- [interpreting-discrepancies.md](interpreting-discrepancies.md) - Analyzing structural differences

## Key Principles

**Structure quality matters**: Always check validation metrics before drawing biological conclusions.

**Context is crucial**: A "bad" region in a structure might be genuinely disordered, not a modeling error.

**Multiple methods**: Use multiple validation approaches; no single metric tells the whole story.

