Status
Community

Here, we introduce eRMSF, a fast and user-friendly Python package built with MDAKit from MD-Analysis, designed to perform ensemble-based Root Mean Square Fluctuation (RMSF) analyses. 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.

eRMSF is bound by a Code of Conduct.

Below we provide instructions for pip installation.

To build the package from source, run:

pip install git+https://github.com/pablo-arantes/ermsfkit.git

or

git clone https://github.com/pablo-arantes/ermsfkit.git
pip install ermsfkit/

Below we provide an example of use:

from eRMSF import ermsfkit
import MDAnalysis as mda
import matplotlib.pyplot as plt
from MDAnalysis.tests.datafiles import PSF, DCD
from MDAnalysis.analysis import align

# Load the trajectory
u = mda.Universe(PSF, DCD)

# Align to the first frame (or average structure)
average = align.AverageStructure(u, u, select='protein and name CA',
                                 ref_frame=0).run()
ref = average.results.universe
align.AlignTraj(u, ref,
                select='protein and name CA',
                in_memory=True).run()

# Select the protein backbone (Cα atoms)
protein = u.select_atoms('protein and name CA')

# Initialize the eRMSF analysis
ermsf_analysis = ermsfkit(protein, skip=1, reference_frame=0)

# Run the analysis
ermsf_analysis.run()

# Extract results
results = ermsf_analysis.results.ermsf

For convenience, we also provide a Google Colab notebook that allows users to run the eRMSF analysis with ease.

- eRMSF calculation with comparison to traditional RMSF.

The eRMSF source code is hosted at https://github.com/pablo-arantes/ermsfkit and is available under the GNU General Public License, version 2 (see the file LICENSE).

Copyright (c) 2025, Pablo Arantes

Project based on the MDAnalysis Cookiecutter version 0.1. Please cite MDAnalysis when using eRMSF in published work.

If you use eRMSF, please cite the respective software and references:

• eRMSF
  Arantes et al., Journal of Chemical Information and Modeling, 2025, DOI: 10.1021/acs.jcim.5c02413