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Implementation of a methodology for determining elastic properties of lipid assemblies from molecular dynamics simulations

Overview of attention for article published in BMC Bioinformatics, April 2016
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Title
Implementation of a methodology for determining elastic properties of lipid assemblies from molecular dynamics simulations
Published in
BMC Bioinformatics, April 2016
DOI 10.1186/s12859-016-1003-z
Pubmed ID
Authors

Niklaus Johner, Daniel Harries, George Khelashvili

Abstract

The importance of the material properties of membranes for diverse cellular processes is well established. Notably, the elastic properties of the membrane, which depend on its composition, can directly influence membrane reshaping and fusion processes as well as the organisation and function of membrane proteins. Determining these properties is therefore key for a mechanistic understanding of how the cell functions. We have developed a method to determine the bending rigidity and tilt modulus, for lipidic assemblies of arbitrary lipid composition and shape, from molecular dynamics simulations. The method extracts the elastic moduli from the distributions of microscopic tilts and splays of the lipid components. We present here an open source implementation of the method as a set of Python modules using the computational framework OpenStructure. These modules offer diverse algorithms typically used in the calculatation the elastic moduli, including routines to align MD trajectories of complex lipidic systems, to determine the water/lipid interface, to calculate lipid tilts and splays, as well as to fit the corresponding distributions to extract the elastic properties. We detail the implementation of the method and give several examples of how to use the modules in specific cases. The method presented here is, to our knowledge, the only available computational approach allowing to quantify the elastic properties of lipidic assemblies of arbitrary shape and composition (including lipid mixtures). The implementation as python modules offers flexibility, which has already allowed the method to be applied to diverse lipid assembly types, ranging from bilayers in the liquid ordered and disordered phases to a study of the inverted-hexagonal phase, and with different force-fields (both all-atom and coarse grained representations). The modules are freely available through GitHub at https://github.com/njohner/ost_pymodules/ while OpenStructure can be obtained at http://www.openstructure.org .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Germany 1 2%
Unknown 51 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 26%
Student > Bachelor 8 15%
Researcher 7 13%
Student > Doctoral Student 3 6%
Professor 3 6%
Other 7 13%
Unknown 11 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 17%
Engineering 8 15%
Physics and Astronomy 7 13%
Chemistry 6 11%
Agricultural and Biological Sciences 5 9%
Other 6 11%
Unknown 12 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 April 2016.
All research outputs
#18,450,346
of 22,860,626 outputs
Outputs from BMC Bioinformatics
#6,326
of 7,294 outputs
Outputs of similar age
#220,303
of 300,876 outputs
Outputs of similar age from BMC Bioinformatics
#96
of 109 outputs
Altmetric has tracked 22,860,626 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
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