The `reweighting` module¶

With the reweighting module, you can use experimental data to reweight your conformational ensemble following the Bayesian/Maximum Entropy (BME) method ^[12].

Fitting to experimental data and calculated ensemble structural properties are presented in a user-friendly interactive graphical dashboard.

Calculations are done for the ensemble before and after reweighting, facilitating comparisons.

Reweight your conformational ensemble using experimental SAXS data¶

To use experimental SAXS data to reweight your conformational ensemble following the BME method, provide Ensemblify with:

CLI Parameter	Description
Trajectory (--trajectory, -trj)	Your generated ensemble in trajectory format.
Topology (--topology, -top)	Your trajectory's corresponding topology file.
Trajectory ID (--trajectoryid, -tid)	Name used to identify your protein in the created graphical dashboard.
Experimental SAXS data (--expdata, -exp)	Experimental SAXS data of your protein.

(ensemblify_env) $ ensemblify reweighting \
    -trj trajectory.xtc \
    -top topology.pdb \
    -tid protein_name \
    -exp exp_SAXS_data.dat

from ensemblify.reweighting import reweight_ensemble

reweight_ensemble(
    'trajectory.xtc',
    'topology.pdb',
    'trajectory_name',
    'exp_SAXS_data.dat'
)

References¶

[12] S. Bottaro , T. Bengsten and K. Lindorff-Larsen, “Integrating Molecular Simulation and Experimental Data: A Bayesian/Maximum Entropy Reweighting Approach,” pp. 219-240, Feb. 2020. In: Z. Gáspári, (eds) Structural Bioinformatics, Methods in Molecular Biology, vol. 2112, Humana, New York, NY. [DOI]