Computationally Efficient Prediction of Area per Lipid

TL;DR

This paper introduces a method to efficiently predict the area per lipid in membranes by leveraging the linear temperature dependence of APL, significantly reducing simulation time.

Contribution

It proposes a novel approach to estimate APL at target temperatures using high-temperature simulations and extrapolation, improving computational efficiency.

Findings

Thermal expansion coefficient can be computed at high temperatures.

Extrapolation reduces sampling time for APL prediction by about 10 times.

Linear dependence of APL on temperature over the entire range.

Abstract

Area per lipid (APL) is an important property of biological and artificial membranes. Newly constructed bilayers are characterized by their APL and newly elaborated force fields must reproduce APL. Computer simulations of APL are very expensive due to slow conformational dynamics. The simulated dynamics increases exponentially with respect to temperature. APL dependence on temperature is linear over an entire temperature range. I provide numerical evidence that thermal expansion coefficient of a lipid bilayer can be computed at elevated temperatures and extrapolated to the temperature of interest. Thus, sampling times to predict accurate APL are reduced by a factor of ~10.