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drug-trajectory-analysis

Analyze protein–ligand MD trajectories to extract RMSD, COM drift, RMSF, hydrogen bonds, and contact occupancy.

144|21|Updated Jan 8, 2026
Search Tags:#protein-ligand#rmsd#hydrogen bonds#md trajectory analysis#pocket rmsf#interaction fingerprints
One-click install
npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill drug-trajectory-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: drug-trajectory-analysis
Source: https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/drug-trajectory-analysis
Command: npx skills add https://github.com/learningmatter-mit/AtomisticSkills --skill drug-trajectory-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires MDAnalysis, matplotlib, numpy, prolif, pymol, and includes scripts (resource) components.

What problem does it solve?

This Skill turns a protein–ligand molecular dynamics (MD) trajectory into quantitative binding-mode descriptors so you can judge pose stability and interaction quality without manual frame-by-frame inspection.

Core Features & Use Cases

  • Ligand pose stability metrics: computes ligand heavy-atom RMSD and ligand center-of-mass (COM) drift over time.
  • Binding-pocket dynamics: estimates pocket residue RMSF to identify flexible contact regions.
  • Interaction quality over time: detects protein–ligand hydrogen bonds, computes residue contact occupancy, and optionally generates protein–ligand interaction fingerprints (IFPs) using ProLIF.
  • Reproducible outputs for decision-making: writes CSVs and a JSON summary suitable for comparing refinement runs and go/no-go assessment.

Quick Start

Run trajectory analysis for ligand residue UNL by executing the command below to produce RMSD, COM drift, RMSF, hydrogen bonds, contacts, optional IFPs, and plots in your specified output directory. python .agents/skills/drug-trajectory-analysis/scripts/analyze_trajectory.py --topology md/system/complex_solvated.pdb --trajectory md/run/production.dcd --ligand_resname UNL --pocket_cutoff 5.0 --output_dir md/analysis/

Frequently Asked Questions about drug-trajectory-analysis

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

FAQPage Schema
How do I calculate ligand RMSD and hydrogen bonds from an MD trajectory?▼

To calculate ligand RMSD and hydrogen bonds from an MD trajectory, use a script that processes topology and trajectory files with MDAnalysis to extract binding-mode stability metrics and outputs the results as CSV files and plots.

What is pocket RMSF and when do I need it for protein-ligand binding analysis?▼

Pocket RMSF is a binding-pocket dynamics metric that estimates pocket residue flexibility to identify flexible contact regions, needed when evaluating protein-ligand interaction quality and pose stability over trajectory time.

Can I generate protein-ligand interaction fingerprints using MDAnalysis and ProLIF?▼

Yes, you can generate protein-ligand interaction fingerprints using MDAnalysis and ProLIF, which are supported dependencies for optionally computing interaction fingerprints alongside hydrogen bonds and residue contact occupancy.

Do I need PyMOL installed to run molecular dynamics trajectory analysis?▼

You need PyMOL installed if you want to utilize optional visualization features within the provided runtime environment, while core trajectory analysis metrics like RMSD and COM drift rely primarily on MDAnalysis and numpy.

What's the best way to extract center-of-mass drift and contact occupancy for drug discovery decision support?▼

The best way to extract center-of-mass drift and contact occupancy for drug discovery decision support is running a deterministic trajectory analysis script that outputs a JSON summary and CSV files suitable for comparing refinement runs and go/no-go assessment.

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