BilayerAnalyzer analysis: thickness_mass_weighted_std - Estimates the thickness using two times the mass-weighted standard deviation of coordinates along the normal.

Description

Estimate the thickness via the mass weighted standard deviation along the normal dimension. This protocol is used to estimate the thickness by computing the standard deviation of the reference atoms (e.g. phosphorous atoms) coordinates along the bilayer normal dimension weighted by their masses: thickness = 2xmass_weighted_std This is same method used by MEMBPLUGIN to estimate bilayer thickness (Blake: I had to examine the MEMBPLUGIN source code to see that this is what it actually does.).

This protocol is identified by the analysis key: ‘mass_weighted_std_thickness’

Initiated by instance of:

<class 'pybilt.bilayer_analyzer.analysis_protocols.MassWeightedStdDistProtocol'>

Syntax

thickness_mass_weighted_std analysis-ID keyword value

  • thickness_mass_weighted_std = analysis-Key - keyword/name for this analysis.

  • analysis-ID = The unique name/ID being assigned to this analysis.

  • keyword value = settings keyword value pairs

    • selection_string (str): Provide the MDAnalysis compatible selection for the atoms to include in this analysis. Default: ‘BILAYER’, use all the lipids of the bilayer as recovered from the selection given to the external BilayerAnalyzer.

Examples

Construct analyzer:

analyzer = BilayerAnalyzer(structure='name_of_structure_file',
                           trajectory='name_of_traj_file',
                           selection='resname POPC DOPC')

Add by string - use default settings:

analyzer.add_analysis('thickness_mass_weighted_std thickness_mass_weighted_std_1')

Add by string - adjust a setting:

analyzer.add_analysis('thickness_mass_weighted_std thickness_mass_weighted_std_1 selection_string name P')

Add by list:

analyzer.add_analysis(list(['thickness_mass_weighted_std', 'thickness_mass_weighted_std_1', dict({'selection_string':'name P'})]))

Add by dict:

analyzer.add_analysis(dict({'analysis_key': 'thickness_mass_weighted_std', 'analysis_id': 'thickness_mass_weighted_std_1','analysis_settings':dict({'selection_string':'name P'})}))

To remove from analyzer:

analyzer.remove_analysis('thickness_mass_weighted_std_1')

Output Info:

Retrieve output after running analyses:

output = analyzer.get_analysis_data('thickness_mass_weighted_std_1')

The output is type <type 'numpy.ndarray'>

Note

The P-P distance can be estimated for phospholipids by assigning the phosphorous atoms as the reference atoms (e.g. with selection: name P).

References

  1. R. Guixa-Gonzalez; I. Rodriguez-Espigares; J. M. Ramirez-Anguita; P. Carrio-Gaspar; H. Martinez-Seara; T. Giorgino; J. Selent. MEMBPLUGIN: studying membrane complexity in VMD. Bioinformatics 2014; vol. 30 (10) p. 1478-1480 doi:10.1093/bioinformatics/btu037