Efficient calculation of orientation-dependent lipid dynamics from membrane simulations

Molecular dynamics simulations of lipid membranes have become increasingly impactful in biophysics because they offer atomistic resolution of structural fluctuations in relation to their functional outputs. Yet quantitative characterization of multiscale processes is a formidable challenge due to the distribution of motions that evade analysis of discrete simulation data. Here we investigate the efficient calculation of CH bond relaxation rates from membrane simulations. Widely used computational approaches offer numerical simplicity but fall short of capturing crucial aspects of the orientation dependence of the dynamics. To circumvent this problem, we introduced a robust framework based on liquid crystal theory which considers explicitly the CH bond motions with respect to the director axis (bilayer normal). Analysis of the orientation dependence of the dynamics shows excellent agreement with experiment, illustrating how the ordering potential affects the calculated relaxation rates. Furthermore, a fit-based resampling of the autocorrelation function of the bond fluctuations validates the new approach for low-temporal resolution data. The recovered relaxation rates indicate that at short timescales, both with and without cholesterol, the local motions of CH bonds describe the bilayer microviscosity and resemble liquid hydrocarbons. Our results establish the critical role of the orientational anisotropy in analysis of membrane simulations, explain fundamental aspects of lipid dynamics, and provide guidelines for extracting information that can be compared to experimental data..

Medienart:

Preprint

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

bioRxiv.org - (2024) vom: 16. Apr. Zur Gesamtaufnahme - year:2024

Sprache:

Englisch

Beteiligte Personen:

Doktorova, Milka [VerfasserIn]
Khelashvili, George [VerfasserIn]
Brown, Michael F [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

570
Biology

doi:

10.1101/2023.05.23.542012

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI039692779