Accurate In Silico Modeling of Asymmetric Bilayers Based on Biophysical Principles. Academic Article uri icon

Overview

abstract

  • Technological advances in the last decade have enabled the study of ever more complex and physiologically relevant model membranes to help dispel the mystery surrounding the role of plasma membrane asymmetry in various cellular processes. The slowly accumulating body of experimental data is fueling renewed interest in and the need for computational methods to support interpretations and address a wide range of problems that are still not amenable to direct experimental study. The specific appeal of molecular dynamics simulations for this purpose lies in their ability to access information at atomic resolution, which is useful for the formulation of testable mechanistic hypotheses. But, the range of questions that can be addressed reliably with such simulations is determined by the appropriate construction and simulation of asymmetric bilayer models. One essential way to achieve this goal is to follow rigorous biophysical criteria and principles. In this context, we show that the requirement for a robust comparison between the properties of simulated asymmetric and symmetric model membranes is for the tension in each bilayer leaflet to be zero. Commonly used methods for constructing asymmetric bilayers, including matching the average areas of the leaflets from the corresponding symmetric systems, do not ensure zero leaflet tension, thus precluding physically realistic changes in the areas of the two leaflets. We present, to our knowledge, a new method for identifying the ideal lipid packing in bilayers with different leaflet compositions that achieves the zero-tension goal, and discuss the basic principles underlying the biophysically correct computational study of asymmetric membranes.

publication date

  • September 15, 2018

Research

keywords

  • Computer Simulation
  • Lipid Bilayers

Identity

PubMed Central ID

  • PMC6224353

Scopus Document Identifier

  • 85054481726

Digital Object Identifier (DOI)

  • 10.1016/j.bpj.2018.09.008

PubMed ID

  • 30297133

Additional Document Info

volume

  • 115

issue

  • 9