coot-model-building

Automate macromolecular refinement workflows in Coot with checkpoints and validation metrics.

166|59|Updated Aug 24, 2015
One-click install
npx skills add https://github.com/pemsley/coot --skill coot-model-building
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: coot-model-building
Source: https://github.com/pemsley/coot/tree/main/mcp/docs/skills/model-building
Command: npx skills add https://github.com/pemsley/coot --skill coot-model-building

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill consolidates best practices for model-building tools and refinement, guiding researchers to implement robust validation workflows and safe refinements in Coot.

Core Features & Use Cases

  • Checkpoint-driven workflow: create and restore named checkpoints to compare alternative refinement strategies.
  • Extended residue selection: refine larger regions around a problem residue to maintain context and improve outcomes.
  • Spatial-neighbour awareness: include nearby residues to account for non-bonded interactions during refinement.
  • Iterative validation: systematically re-check Ramachandran, rotamer, and density metrics after each adjustment.
  • Safe navigation: center on residues and manage refinements with undo/restore to prevent irreversible changes.

Quick Start

Start by centering on a problematic residue, create a named checkpoint, perform an initial refinement over a larger region (e.g., ±1-2 neighbors), then evaluate Ramachandran, rotamer, and density metrics and iterate as needed.

Frequently Asked Questions about coot-model-building

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I improve macromolecular refinement outcomes for problematic residues in Coot?

Macromolecular refinement in Coot improves by selecting extended residue regions around problematic residues, maintaining spatial context to account for non-bonded interactions during model-building. This spatial-neighbour awareness prevents localized distortions and yields better density fit.

What is the best way to validate model quality after each adjustment in Coot?

Model validation in Coot requires iteratively re-checking Ramachandran plots, rotamer geometry, and density metrics after every refinement adjustment. This systematic re-evaluation ensures structural errors are caught immediately rather than propagating through subsequent building steps.

Can I create checkpoints to compare alternative refinement strategies during model-building?

Checkpoints can be created and restored during model-building to compare alternative refinement strategies in Coot. Named checkpoints allow researchers to test different approaches, evaluate validation metrics, and safely roll back to previous states if outcomes degrade.

Does Coot support undo and restore to prevent irreversible changes during macromolecular model-building?

Coot supports safe rollback via undo and restore functions during macromolecular model-building. These features, combined with mandatory checkpoints, ensure that refinement adjustments are never irreversible, allowing researchers to navigate structures and test changes without risk.

When do I need to include spatial neighbours during macromolecular refinement?

Spatial neighbours must be included during macromolecular refinement when a problem residue has close non-bonded interactions. Refining a larger region of ±1-2 neighbors maintains structural context, preventing steric clashes and improving the overall geometry of the model.

What limitations exist when using extended residue selections for macromolecular model-building?

Extended residue selections in macromolecular model-building require careful checkpoint management because larger refinement regions increase computational complexity. While including spatial neighbours improves contextual accuracy, researchers must balance selection size against validation speed and density metric reliability.