design-comparison

Compare, rank, and batch-visual QC protein design candidates in PyMOL.

3|Updated Jan 28, 2026
One-click install
npx skills add https://github.com/ANaka/claudemol --skill design-comparison
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: design-comparison
Source: https://github.com/ANaka/claudemol/tree/main/claude-plugin/skills/design-comparison
Command: npx skills add https://github.com/ANaka/claudemol --skill design-comparison

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Compare, rank, and batch-visual QC multiple protein design candidates in PyMOL.

Core Features & Use Cases

  • Batch loading and side-by-side visualization of multiple designs
  • Ranking designs by metrics (mean pLDDT, RMSD, length)
  • Iteration tracking across design rounds and overlays with a template or AF2 predictions
  • Design vs. template/AF2 overlays and quality checks

Quick Start

Load your designs into PyMOL and run the built-in ranking workflow to see the top candidates.

Frequently Asked Questions about design-comparison

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

FAQPage Schema
How do I rank and compare multiple protein designs in PyMOL?

You can batch load multiple protein design PDBs into PyMOL and run a ranking workflow to compare candidates by mean pLDDT, RMSD, and length, exporting a ranked list of top designs.

Can I overlay AF2 predictions with a template for visual QC of protein designs?

Yes, you can overlay template structures or AlphaFold predictions with your design candidates in PyMOL to perform side-by-side visual quality control and check structural alignment.

What is the best way to evaluate RFdiffusion or ProteinMPNN design iterations?

Evaluating RFdiffusion and ProteinMPNN design iterations is done by tracking design rounds, overlaying candidates with templates, and computing pLDDT-based scores and RMSD to rank quality.

Does this protein design ranking workflow require external dependencies?

No external dependencies are required. The workflow operates entirely within PyMOL to load PDBs, compute structural metrics like RMSD and pLDDT, and export the ranked design results.

How do I calculate RMSD and pLDDT scores for batch-loaded protein structures?

Loading multiple protein structures into PyMOL allows the workflow to automatically compute RMSD against templates and calculate mean pLDDT scores to generate a ranked comparison of all candidates.

Why use PyMOL for batch visual QC of protein design candidates instead of other tools?

Using PyMOL for batch visual QC enables direct side-by-side visualization, template overlays, and integrated metric calculation like RMSD and pLDDT, streamlining the ranking of multiple design variants.