drug-redocking-rmsd

Compute symmetry-corrected heavy-atom RMSD between docked poses and reference ligands.

144|21|Updated Jan 8, 2026
One-click install
npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill drug-redocking-rmsd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: drug-redocking-rmsd
Source: https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/drug-redocking-rmsd
Command: npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill drug-redocking-rmsd

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires rdkit, meeko, numpy, and includes scripts (resource) components.

What problem does it solve?

This Skill determines whether an AI docking protocol can reliably reproduce a crystallographic ligand pose by computing symmetry-corrected heavy-atom RMSD between docked poses and a reference ligand.

Core Features & Use Cases

  • Symmetry-corrected in-place heavy-atom RMSD: Computes the minimum heavy-atom RMSD over molecular automorphisms without rigid-body alignment to ensure docking-valid “in-place” validation.
  • Top-poses protocol gate: Produces a pass/fail verdict based on whether the top-scored pose (pose 1) falls below a configurable RMSD threshold.
  • Ligand identity safety check: Verifies reference and docked compounds match via InChIKey connectivity so the result cannot silently compare unrelated molecules.
  • Handles common reference formats: Accepts reference ligands as PDB (requires SMILES for bond-order assignment) or SDF (bond orders included).

Quick Start

Compute the RMSD gate by running the Skill’s compute_rmsd.py on your Vina multi-model PDBQT and a crystal reference ligand file, supplying SMILES if the reference is a PDB.

Frequently Asked Questions about drug-redocking-rmsd

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

FAQPage Schema
How do I calculate symmetry-corrected RMSD for docking validation?▼

Symmetry-corrected RMSD for docking validation computes the minimum heavy-atom RMSD over molecular automorphisms without rigid-body alignment, ensuring docked poses are evaluated accurately against a crystallographic reference ligand.

What is in-place heavy-atom RMSD and when do I need it for virtual screening?▼

In-place heavy-atom RMSD measures pose reproduction accuracy without rigid-body alignment. It is needed for virtual screening quality gates where you must verify a docking protocol recovers a crystallographic ligand pose.

How do I validate Vina docking poses against a crystal reference ligand?▼

You validate Vina docking poses by running a symmetry-corrected RMSD calculation on multi-model PDBQT files against a reference ligand, producing a pass/fail gate based on whether pose 1 meets your RMSD threshold.

Does RDKit CalcRMS support PDB and SDF reference ligands for self-docking checks?▼

Yes, the reference ligand for self-docking checks can be provided as PDB, which requires SMILES for bond-order assignment, or SDF, which includes bond orders directly, using RDKit CalcRMS for symmetry-corrected RMSD.

Why does my docking validation fail when comparing unrelated ligand poses?▼

Docking validation fails for unrelated ligands because an InChIKey connectivity identity check verifies the reference and docked compounds match, preventing silent comparisons of structurally different molecules during RMSD calculation.