Abstract
Many biological processes involve large-scale changes in membrane shape. Computer simulations of these processes are challenging since they occur across a wide range of spatiotemporal scales that cannot be investigated in full by any single current simulation technique. A potential solution is to combine different levels of resolution through a multiscale scheme. Here, we present a multiscale algorithm that backmaps a continuum membrane model represented as a dynamically triangulated surface (DTS) to its corresponding molecular model based on the coarse-grained (CG) Martini force field. Thus, we can use DTS simulations to equilibrate slow large-scale membrane conformational changes and then explore the local properties at CG resolution. We demonstrate the power of our method by backmapping a vesicular bud induced by binding of Shiga toxin and by transforming the membranes of an entire mitochondrion to near-atomic resolution. Our approach opens the way to whole cell simulations at molecular detail.
Highlights
Many biological processes involve large-scale changes in membrane shape
dynamically triangulated surface (DTS) and similar approaches are successful in describing the shape of simple membranes[17,20,21,22], but their predictions are limited for realistic cellular membranes as the precise molecular ingredients become essential
As an attempt to resolve this limitation, we have developed an algorithm, coined TS2CG (Supplementary Note), that backmaps a DTS structure to a CG representation
Summary
Many biological processes involve large-scale changes in membrane shape. Computer simulations of these processes are challenging since they occur across a wide range of spatiotemporal scales that cannot be investigated in full by any single current simulation technique. AAMD and CG-MD together do not cover the full scale that is required to investigate membrane-remodeling processes This shortcoming of AA-MD and CG-MD has pushed the modeling community to use continuum models that are based on macroscopic phenomenological equations that involve only a few model parameters, e.g., dynamical triangulated surfaces (DTS) simulations[15,16,17,18,19]. DTS and similar approaches are successful in describing the shape of simple membranes[17,20,21,22], but their predictions are limited for realistic cellular membranes as the precise molecular ingredients (protein–protein and protein–lipid interactions) become essential To overcome these discrepancies, continuum techniques have been coupled in a multiscale scheme, in which the predictions of high-resolution models (i.e., AA or CG-MD) provide inputs for the large-scale model[23,24,25,26]. We discuss possible routes for further development
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