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arXiv · 2010.00561

SiMPLISTIC: A Novel Pairwise Potential for Implicit Solvent Lipid Simulations with Single-site Models

Abstract

Implicit solvent, coarse-grained models with pairwise interactions can access the largest length and time scales in molecular dynamics simulations, owing to the absence of interactions with a huge number of solvent particles, the smaller number of interaction sites in the model molecules, and the lack of fast sub-molecular degrees of freedom. In this paper, we describe a maximally coarse-grained model for lipids in implicit water. The model is called SiMPLISTIC, which abbreviates for Single-site Model with Pairwise interaction for Lipids in Implicit Solvent with Tuneable Intrinsic Curvature. SiMPLISTIC lipids rapidly self-assemble into realistic non-lamellar and lamellar phases such as inverted micelles and bilayers, the spontaneous curvature of the phase being determined by a single free parameter of the model. Model membrane simulations with the lamellar lipids show satisfactory fluid and gel phases with no interdigitation or tilt. The model lipids follow rigid body dynamics suggested by empirical studies, and generate bilayer elastic properties consistent with experiments and other simulations. SiMPLISTIC can also simulate mixtures of lipids that differ in their packing parameter or length, the latter leading to the phenomenon of hydrophobic mismatch driven domain formation. The model has a large scope due to its speed, conceptual and computational simplicity, and versatility. Applications may range from large-scale simulations for academic and industrial research on various lipid-based systems, such as lyotropic liquid crystals, biological and biomimetic membranes, vectors for drug and gene delivery, to fast, lightweight, interactive simulations for gaining insights into self-assembly, lipid polymorphism, biomembrane organization etc.

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BibTeXRIS

Somajit Dey, Jayashree Saha. 2020-10-01. SiMPLISTIC: A Novel Pairwise Potential for Implicit Solvent Lipid Simulations with Single-site Models. https://doi.org/10.1016/j.jciso.2021.100004

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