FastMDAnalysis: Software for Automated Analysis of Molecular Dynamics Trajectories
CSEF · 2026 Computational Science (Senior Division)
Overview
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 essential structural and dynamics analyses, including root-mean-square deviation and fluctuation, radius of gyration, hydrogen bonding, solvent-accessible surface area, and secondary structure assignment, together with dimensionality reduction and clustering algorithms, within a single, consistent environment built on MDTraj, scikit-learn, and SciPy. We demonstrate a >90% 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.
Competition history
- CSEF 2026
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