mdanalysis-trajectory
Analyze MD trajectories from GROMACS, AMBER, NAMD, CHARMM, LAMMPS. Reads topology/trajectory into Universe objects; supports RMSD, RMSF, radius of gyration, contact maps, H-bonds, PCA, and custom distance/angle calculations. Use for post-simulation structural analysis; use OpenMM/GROMACS for running simulations.
npx skills add BioTender-max/awesome-bio-agent-skills --skill mdanalysis-trajectory --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# MDAnalysis — Molecular Dynamics Trajectory Analysis ## Overview MDAnalysis provides a uniform Python interface for reading and analyzing molecular dynamics trajectories regardless of MD engine (GROMACS, AMBER, NAMD, CHARMM, LAMMPS, OpenMM). It represents molecular systems as `Universe` objects containing an `AtomGroup` with positions, velocities, forces, and topology data. Trajectories are iterated frame-by-frame or analyzed in bulk using analysis modules for RMSD, RMSF, radius of gyration, hydrogen bonds, solvent-accessible surface area, and PCA. MDAnalysis integrates with NumPy, pandas, and matplotlib, making it the standard tool for post-simulation structural analysis in computational chemistry and drug discovery. ## When to Use - Computing RMSD and RMSF of protein backbone or specific residue groups after MD simulation - Analyzing ligand binding stability: pocket RMSD, contact persistence, hydrogen bond occupancy - Performing principal component analysis (PCA) on trajectory conformations - Computing solvent-accessible surface area (SASA), radius of gyration, and end-to-end distance - Extracting representative cluster structures from long MD trajectories for visualization - Us
- Overview
- When to Use
- Prerequisites
- Quick Start
- Core API
- Module 1: Universe and AtomGroup — Loading and Selecting Atoms
- Module 2: Trajectory Iteration — Per-Frame Analysis
- Module 3: RMSD Analysis — Structural Drift Over Time
- Module 4: RMSF Analysis — Per-Residue Flexibility
- Module 5: Hydrogen Bond Analysis
- Module 6: PCA and Conformational Clustering
- Key Parameters
- Common Workflows
- Workflow 1: Complete Protein-Ligand Binding Stability Analysis
Install MDAnalysis pip install MDAnalysis Install with all analysis extras pip install "MDAnalysis[analysis]" Verify python -c "import MDAnalysis as mda; print(mda.__version__)"
What does the mdanalysis-trajectory skill do?
Analyze MD trajectories from GROMACS, AMBER, NAMD, CHARMM, LAMMPS. Reads topology/trajectory into Universe objects; supports RMSD, RMSF, radius of gyration, contact maps, H-bonds, PCA, and custom distance/angle calculations. Use for post-simulation structural analysis; use OpenMM/GROMACS for running simulations.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill mdanalysis-trajectory --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 144 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.