Get RMSF#

Calculating root-mean-square fluctuations per atom over a trajectory.

The function molsysmt.structure.get_rmsf() computes the root-mean-square fluctuation (RMSF) of each atom around its time-averaged spatial position across a trajectory or structural ensemble.

Added in version 1.0.0.

API documentation

Follow this link for a detailed description of the input arguments, raised errors, and returned objects of this function: molsysmt.structure.get_rmsf().

Basic usage#

Let’s show how to calculate atomic fluctuations over a pentalanine simulation (first superposing all frames onto the reference frame to isolate pure internal flexibility from rigid-body tumbling):

import molsysmt as msm
import matplotlib.pyplot as plt
import pyunitwizard as puw
import numpy as np

molsys = msm.convert(msm.systems['pentalanine']['traj_pentalanine.h5msm'])
molsys_fitted = msm.structure.least_rmsd_fit(molsys, selection='all', selection_fit='backbone', reference_structure_index=0)

Note

Demo Systems Catalog

This tutorial uses demonstration datasets provided by MolSysMT. To explore the full catalog of bundled systems, forms, and file paths, visit the Demo Systems guide.

We calculate the RMSF across all atoms using molsysmt.structure.get_rmsf():

rmsf_all = msm.structure.get_rmsf(molsys_fitted, selection='all')

print('RMSF array shape:', rmsf_all.shape)
print(f'Average RMSF over all atoms: {rmsf_all.mean():.4f}')

RMSF array shape: (62,)
Average RMSF over all atoms: 0.2551 nanometer

Plotting per-atom fluctuation profile#

We plot the RMSF profile along all atom indices to identify regions of elevated atomic flexibility:

rmsf_val = puw.get_value(rmsf_all, to_unit='nm')

plt.figure(figsize=(9, 4.5))
plt.plot(range(len(rmsf_val)), rmsf_val, marker='o', color='teal', lw=1.5, markersize=4, label='All Atoms RMSF')
plt.xlabel('Atom Index')
plt.ylabel('RMSF (nm)')
plt.title('Root-Mean-Square Fluctuations Profile')
plt.grid(True, linestyle='--', alpha=0.5)
plt.legend()
plt.tight_layout()
plt.show()

Per-residue fluctuation analysis#

We can compute the average fluctuation for each residue group to assess backbone and sidechain mobility by residue:

groups = msm.get(molsys, element='group', atom_index=True)
group_names = msm.get(molsys, element='group', name=True)
res_rmsf = [np.mean(rmsf_val[atom_idx]) for atom_idx in groups]

plt.figure(figsize=(8, 4))
plt.bar(range(len(res_rmsf)), res_rmsf, color='steelblue', edgecolor='black', alpha=0.85, width=0.6)
plt.xticks(range(len(res_rmsf)), [f'{name}_{i}' for i, name in enumerate(group_names)])
plt.xlabel('Residue')
plt.ylabel('Mean RMSF (nm)')
plt.title('Mean Fluctuation per Residue')
plt.grid(axis='y', linestyle='--', alpha=0.5)
plt.tight_layout()
plt.show()

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