BilayerAnalyzer analysis: `thickness_grid` - Bilayer thickness using lipid_grid.¶

Description¶

Estimate the bilayer thickness using a gridding procedure.

This analysis uses a lipid grid representation (lipid positions are mapped to 2-D grids, one grid per leaflet) of the bilayer to estimate the bilayer thickness. This is done by measuring the difference in ‘z’ position between corresponding grid points of opposing bilayer leaflets.

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

Initiated by instance of:¶

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

Syntax¶

thickness_grid analysis-ID

thickness_grid = analysis-Key - keyword/name for this analysis.
analysis-ID = The unique name/ID being assigned to this analysis.

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_grid thickness_grid_1') 

Add by string - adjust a setting:

analyzer.add_analysis('thickness_grid thickness_grid_1 none None')

Add by list:

analyzer.add_analysis(list(['thickness_grid', 'thickness_grid_1', dict({'none':None})]))

Add by dict:

analyzer.add_analysis(dict({'analysis_key': 'thickness_grid', 'analysis_id': 'thickness_grid_1','analysis_settings':dict({'none':None})}))

To remove from analyzer:

analyzer.remove_analysis('thickness_grid_1')

Output Info:¶

Retrieve output after running analyses:

output = analyzer.get_analysis_data('thickness_grid_1')

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

Note

The P-P distance can be estimated for phospholipid by assigning positions of the phosphorous atoms to the lipid grid.

References¶

Allen et al. Vol. 30, No. 12 Journal of Computational Chemistry
Gapsys et al. J Comput Aided Mol Des (2013) 27:845-858

BilayerAnalyzer analysis: thickness_grid - Bilayer thickness using lipid_grid.¶