scientific-md-simulation

Compute RMSD, RMSF, radius of gyration, hydrogen bonds, and SASA from molecular dynamics trajectories.

3|1|Updated Feb 11, 2026

Search Tags:#trajectory #rmsd #rmsf #md-analysis #mdsimulation #sasa

Ready to run

npx skills add https://github.com/nahisaho/satori --skill scientific-md-simulation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-md-simulation
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-md-simulation
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-md-simulation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze and interpret molecular dynamics trajectories by computing key structural metrics across time, enabling rigorous assessment of stability and interactions.

Core Features & Use Cases

RMSD/RMSF/Rg time-series to quantify structure deviations and flexibility.
Hydrogen bonds & SASA analyses to evaluate interactions and solvent exposure in protein-ligand systems.
OpenFF parameterization for ligand force-field generation to support end-to-end MD workflows.
Use Case: Assess stability of a protein-ligand complex over a 100 ns trajectory and extract per-frame metrics for publication-ready figures.

Quick Start

Run the MD analysis pipeline on your trajectory to compute RMSD, RMSF, Rg, H-bonds, and SASA.

Frequently Asked Questions about scientific-md-simulation

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

FAQPage Schema

How do I compute RMSD and RMSF time-series from a molecular dynamics trajectory?▼

To compute RMSD and RMSF time-series from a molecular dynamics trajectory, apply an analysis pipeline to standard formats like DCD/XTC/TRR and PSF/PDB. The process calculates per-frame structural deviations and flexibility, outputting consolidated time-series metrics for stability assessment.

What metrics are used to evaluate protein-ligand interactions and solvent exposure in MD simulations?▼

Hydrogen bonds and Solvent Accessible Surface Area (SASA) are key metrics used to evaluate protein-ligand interactions and solvent exposure in MD simulations. Analyzing these alongside radius of gyration provides per-frame time-series data to rigorously assess complex stability.

Can I analyze DCD and XTC trajectory files with a PSF topology?▼

Yes, you can analyze DCD and XTC trajectory files using a PSF topology. The analysis supports standard trajectory and topology formats including TRR and PDB, enabling comprehensive structural evaluations like radius of gyration and SASA for protein-ligand systems.

How do I generate ligand force-field parameters for an MD workflow?▼

To generate ligand force-field parameters for an MD workflow, apply OpenFF parameterization to the ligand structure. This process supports end-to-end MD workflows by producing the necessary force-field parameters for rigorous simulation and analysis.

What is the best way to extract per-frame metrics from a 100 ns protein-ligand trajectory?▼

The best way to extract per-frame metrics from a 100 ns protein-ligand trajectory is running a comprehensive MD analysis pipeline. It computes RMSD, RMSF, Rg, hydrogen bonds, and SASA, producing publication-ready per-frame time-series and a consolidated summary.