eRMSF: A Python Package for Ensemble-Based RMSF Analysis of Biomolecular Systems

Understanding molecular flexibility and dynamics across different structural ensembles is essential for interpreting the behavior of complex biological systems. Here, we introduce eRMSF, a fast and user-friendly Python package built with MDAKit from MDAnalysis, designed to perform ensemble-based root mean square fluctuation (RMSF) analyses. Unlike traditional approaches limited to molecular dynamics trajectories, eRMSF extends flexibility analysis to ensembles generated by different methods, such as MD simulations, BioEmu (a deep learning tool for equilibrium ensemble prediction), subsampled AlphaFold2 (AlphaFold ensemble generation), and other computational or experimental sources. By enabling RMSF calculations across heterogeneous ensembles, eRMSF provides a unified framework to evaluate residue or atomic fluctuations in both simulated and predicted structures. Users can easily customize atom, residue, or region selections, tailoring analyses to specific research questions. This approach delivers high-resolution insights into localized motions, complements global stability assessments, and reveals dynamic regions often overlooked by single-method analyses. The repository for eRMSF is available at https://github.com/pablo-arantes/ermsfkit.

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Journal
Journal of Chemical Information and Modeling
Published
2025-11-19
DOI
https://doi.org/10.1021/acs.jcim.5c02413
Primary Topic
Protein Structure and Dynamics
Type
article
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article

eRMSF: A Python Package for Ensemble-Based RMSF Analysis of Biomolecular Systems

Pablo R. Arantes, Rodrigo Ligabue‐Braun, Conrado Pedebos
Journal of Chemical Information and Modeling
Protein Structure and Dynamics
article

eRMSF: A Python Package for Ensemble-Based RMSF Analysis of Biomolecular Systems

Pablo R. Arantes, Rodrigo Ligabue‐Braun, Conrado Pedebos
article en

Abstract

Understanding molecular flexibility and dynamics across different structural ensembles is essential for interpreting the behavior of complex biological systems. Here, we introduce eRMSF, a fast and user-friendly Python package built with MDAKit from MDAnalysis, designed to perform ensemble-based root mean square fluctuation (RMSF) analyses. Unlike traditional approaches limited to molecular dynamics trajectories, eRMSF extends flexibility analysis to ensembles generated by different methods, such as MD simulations, BioEmu (a deep learning tool for equilibrium ensemble prediction), subsampled AlphaFold2 (AlphaFold ensemble generation), and other computational or experimental sources. By enabling RMSF calculations across heterogeneous ensembles, eRMSF provides a unified framework to evaluate residue or atomic fluctuations in both simulated and predicted structures. Users can easily customize atom, residue, or region selections, tailoring analyses to specific research questions. This approach delivers high-resolution insights into localized motions, complements global stability assessments, and reveals dynamic regions often overlooked by single-method analyses. The repository for eRMSF is available at https://github.com/pablo-arantes/ermsfkit.

Journal of Chemical Information and ModelingVol. 65(23)
Universidade Federal de Ciências da Saúde de Porto Alegre (BR)
Openalex Percentile: Top 69%
Protein Structure and Dynamics
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eRMSF: A Python Package for Ensemble-Based RMSF Analysis of Biomolecular Systems — Pablo R. Arantes, Rodrigo Ligabue‐Braun, et al. · Journal of Chemical Information and Modeling (2025) | TGRS Research Map | TGRS