Lipid Depletion-Enrichment Index

Classes

class lipyds.analysis.dei.LipidEnrichment(universe: Union[MDAnalysis.core.groups.AtomGroup, MDAnalysis.core.universe.Universe], select_protein: str = 'protein', cutoff: float = 6, distribution: str = 'binomial', buffer: float = 0, beta: float = 4, **kwargs)[source]

Calculate the lipid depletion-enrichment index around a protein by leaflet.

The depletion-enrichment index (DEI) of a lipid around a protein indicates how enriched or depleted that lipid in the lipid annulus around the protein, with respect to the density of the lipid in the bulk membrane.

The results of this analysis contain these values:

  • ‘Near protein’: the number of lipids \(L\) within

    cutoff \(r\) of the protein

  • ‘Fraction near protein’: the fraction of the lipids \(L\)

    with respect to all lipids within cutoff \(r\) of the protein: \(\frac{n(x_{(L, r)})}{n(x_r)}\)

  • ‘Enrichment’: the depletion-enrichment index.

The hard-cutoff, gaussian distribution algorithm was obtained from [Corradi2018]. The soft-cutoff, binomial distribution algorithm was first published in [Wilson2021]. Please cite them if you use this analysis in published work.

Parameters
  • universe (Universe or AtomGroup) – The atoms to apply this analysis to.

  • select (str (optional)) – A Universe.select_atoms() selection string for atoms that define the lipid head groups, e.g. “name PO4” or “name P*”

  • select_protein (str (optional)) – Selection string for the protein.

  • cutoff (float (optional)) – Cutoff in ångström

  • buffer (float (optional)) – buffer zone length in ångström. If > 0, this means a soft cutoff is implemented.

  • beta (float (optional)) – beta controls the sharpness of soft-cutoff.

  • distribution (str (optional)) – Whether to use the binomial or gaussian distribution

  • **kwargs – Passed to LeafletAnalysisBase.

Variables
  • dei_by_leaflet (list of dicts) – A list of dictionaries of time series data for each leaflet. The first dictionary is for the first leaflet, etc. Leaflets are sorted by z-coordinate; the first leaflet has the lowest z-coordinate.

  • leaflets_summary (list of dicts) – A list of summary dictionaries for each leaflet. The first dictionary is for the first leaflet, etc.

summary_as_dataframe()[source]

Convert the results summary into a pandas DataFrame.

This requires pandas to be installed.