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proteinmpnn-viz

Visualize ProteinMPNN/LigandMPNN design outputs in PyMOL, highlighting designed versus fixed residues.

3|Updated Jan 28, 2026
Search Tags:#visualization#sequence-design#proteinmpnn#ligandmpnn#pymol#residue-confidence#backbone-analysis
One-click install
npx skills add https://github.com/ANaka/claudemol --skill proteinmpnn-viz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: proteinmpnn-viz
Source: https://github.com/ANaka/claudemol/tree/main/claude-plugin/skills/proteinmpnn-viz
Command: npx skills add https://github.com/ANaka/claudemol --skill proteinmpnn-viz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps researchers visualize ProteinMPNN/LigandMPNN outputs in PyMOL, distinguishing designed residues from fixed ones and showing per-position confidence to streamline design validation.

Core Features & Use Cases

  • Visualization of designed vs fixed residues colored by status
  • Per-position confidence mapping to color scales or B-factors
  • Integration with upstream/downstream tools (rfdiffusion-viz and alphafold-validation)
  • Quick inspection of multiple designs on the same backbone

Quick Start

Load your ProteinMPNN output PDB into PyMOL and begin visualizing residue design status and per-position confidence.

Frequently Asked Questions about proteinmpnn-viz

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

FAQPage Schema
How do I visualize ProteinMPNN designed versus fixed residues in PyMOL?▼

Per-position confidence from ProteinMPNN or LigandMPNN outputs is visualized by mapping confidence values to color scales or B-factors within PyMOL, enabling quick inspection of multiple designs on the same backbone.

Can I inspect multiple ProteinMPNN designs on the same backbone?▼

Yes, you can inspect multiple ProteinMPNN designs on the same backbone by loading the output PDBs into PyMOL, facilitating quick residue-level comparisons and per-position confidence assessments across designs.

Does this visualization workflow support LigandMPNN outputs?▼

Yes, the visualization workflow supports LigandMPNN outputs alongside ProteinMPNN, allowing researchers to distinguish designed from fixed residues and assess per-position confidence for both sequence design methods.

What do I need to start visualizing ProteinMPNN design outputs?▼

To start visualizing ProteinMPNN design outputs, you need PyMOL, PDB output files from ProteinMPNN or LigandMPNN, and an environment compatible with the proteinmpnn-viz workflow for loading and rendering structures.

How do I integrate ProteinMPNN visualization with downstream validation tools?▼

ProteinMPNN visualization integrates with downstream validation tools like alphafold-validation and upstream rfdiffusion-viz, enabling a cohesive protein design pipeline from backbone generation through sequence design and structural validation.

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