FastMDAnalysis: Software for Automated Analysis of Molecular Dynamics Trajectories

ABSTRACT The analysis of molecular dynamics (MD) trajectories remains fragmented, requiring researchers to integrate multiple computational methods in bespoke scripts. This creates a significant barrier to reproducibility and limits analytical scope. We present FastMDAnalysis , a unified framework that establishes a reproducible, automated workflow for end‐to‐end trajectory analysis. The system orchestrates a comprehensive and extensible suite of core analysis modules, including root‐mean‐square deviation and fluctuation, radius of gyration, hydrogen bonding, solvent‐accessible surface area, secondary structure assignment, dimensionality reduction, clustering, fraction of native contacts for protein folding studies, and dihedral angle analysis, within a single, consistent environment built on MDTraj , scikit‐learn , and SciPy . The software natively supports all major trajectory formats, including GROMACS , AMBER , and CHARMM . We demonstrate a reduction in code volume for standard workflows and validate its numerical equivalence to reference implementations. FastMDAnalysis provides a methodological advance that makes rigorous, multi‐analysis MD studies accessible and reproducible for the computational chemistry, biology, and biophysics communities. The software is freely available under the MIT license at https://github.com/aai‐research‐lab/fastmdanalysis .