ligandmpnn

Designs ligand-aware protein sequences for structure-guided binding pocket optimization.

25|5|Updated Mar 22, 2026
One-click install
npx skills add https://github.com/zongtingwei/Bioclaw_Skills_Hub --skill ligandmpnn-zongtingwei
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ligandmpnn
Source: https://github.com/zongtingwei/Bioclaw_Skills_Hub/tree/main/skills/protein-design/skills/ligandmpnn
Command: npx skills add https://github.com/zongtingwei/Bioclaw_Skills_Hub --skill ligandmpnn-zongtingwei

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Ligand-aware protein design enables tailoring protein sequences to accommodate and optimize small-molecule ligands within binding pockets, improving binding potential and functional outcomes.

Core Features & Use Cases

  • Ligand-context aware sequence design: integrate ligand presence to guide amino acid choices at binding pockets.
  • Structure-guided design workflow: supports enzyme active sites, metal coordination, and cofactor-binding scenarios.
  • Handoff-ready outputs: designed sequences with context annotations and recommended validation steps for downstream QC.

Quick Start

Generate ligand-contextual protein designs given a backbone and ligand placement.

Frequently Asked Questions about ligandmpnn

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

FAQPage Schema
What is ligand-aware protein design and how does it work?

Ligand-aware protein design tailors protein sequences to accommodate small molecules within binding pockets. It works by incorporating ligand context into sequence optimization, guiding amino acid choices to improve binding potential and functional outcomes.

How do I design protein sequences around a specific small molecule backbone?

To design protein sequences around a small molecule backbone, you provide the protein backbone, ligand context, and residue constraints. The process outputs designed sequences and design plans optimized for ligand binding and downstream validation.

Can I use structure-guided sequence design for metal coordination and cofactor binding?

Yes, structure-guided sequence design supports metal coordination and cofactor-binding scenarios. It integrates ligand presence to guide amino acid choices specifically for enzyme active sites and complex binding pockets.

What inputs are required for ligand-contextual protein design?

Ligand-contextual protein design requires a protein backbone, ligand context, and residue constraints as inputs. These elements define the structural framework and spatial boundaries for the sequence optimization process.

What outputs do I get from a ligand-aware inverse folding workflow?

A ligand-aware inverse folding workflow outputs designed sequences with context annotations and recommended validation steps. These handoff-ready outputs provide design plans specifically formatted for downstream quality control.

Does this sequence design approach work for enzyme active site optimization?

Yes, this sequence design approach works for enzyme active site optimization. It applies structure-guided workflows to tailor sequences around small molecules, metals, or cofactors within the active site binding pocket.