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pose-validation

Validate protein-ligand poses with PoseBusters for physical validity and strain energy.

6|2|Updated Jun 11, 2026
Search Tags:#computational chemistry#protein-ligand docking#pose validation#AI docking#chemical biology
One-click install
npx skills add https://github.com/pradyumnasagar/open-research-skills --skill pose-validation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pose-validation
Source: https://github.com/pradyumnasagar/open-research-skills/tree/main/skills/chemoinformatics/pose-validation
Command: npx skills add https://github.com/pradyumnasagar/open-research-skills --skill pose-validation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires posebusters, rdkit, pandas, posecheck, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Validates docked protein-ligand poses for physical validity and energy reasonableness, ensuring accurate and reliable AI docking results.

Core Features & Use Cases

  • Pose Validation: Utilizes PoseBusters to check geometric constraints and energy values of docked poses.
  • Energy Reasonableness: Quantifies ligand strain in a docked pose and ranks candidates based on total strain.
  • Use Case: After AI docking, use this skill to filter out poses with high strain energy, ensuring only valid and useful poses are analyzed further.

Quick Start

Run the pose-validation skill with the input files 'predicted.sdf' (ligand) and 'receptor.pdb' (receptor) to validate the poses.

Frequently Asked Questions about pose-validation

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

FAQPage Schema
How do I validate protein-ligand poses from AI docking outcomes?▼

You validate protein-ligand poses by running the pose-validation skill with your predicted ligand SDF and receptor PDB files to check geometric constraints and quantify strain energy.

What is ligand strain energy quantification in computational chemistry?▼

Ligand strain energy quantification measures the physical viability of docked poses by calculating total strain, allowing researchers to filter out high-energy conformations before SAR studies.

Can I use PoseBusters to validate poses from DiffDock, EquiBind, and NeuralPLexer?▼

Yes, you can use PoseBusters to validate AI-docking outcomes from tools like DiffDock, EquiBind, and NeuralPLexer to ensure their predicted poses meet geometric and energy criteria.

How do I filter docked poses with high strain energy for chemical biology?▼

Filter docked poses by quantifying ligand strain energy and ranking candidates based on total strain, ensuring only physically valid and useful poses are analyzed further in chemical biology.

What file formats do I need for protein-ligand pose validation?▼

You need a predicted.sdf file for the ligand and a receptor.pdb file for the receptor to run the pose-validation skill and check physical validity and energy reasonableness.

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