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Updated: Sep 2, 2026

Realistic Membrane Modeling Using Complex Lipid Mixtures in Simulation Studies
Published on: September 1, 2023
Membrane mechanics and organization in Martini 2, 3, and CHARMM36 force fields
Elio A Cino1, D Peter Tieleman1
1Centre for Molecular Simulation and Department of Biological Sciences, University of Calgary, Calgary, Alberta T2N 1N4, Canada.
Abstract:
Understanding the accuracies and limitations of force fields is essential for obtaining reliable results from molecular dynamics simulations. In this work, lipid bilayer properties were systematically compared across three commonly used models: Martini 2 (M2), Martini 3 (M3) with the latest lipid parameters, and CHARMM36 (C36). Homogeneous bilayers of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine, 1,2-dioleoyl-sn-glycero-3-phosphocholine, 1,2-dipalmitoyl-sn-glycero-3-phosphocholine, and 1,2-dimyristoyl-sn-glycero-3-phosphocholine, as well as an asymmetric 8-lipid plasma membrane model (PM8), were simulated for up to 30 μs each (aggregate 480 μs). Key properties evaluated include area per lipid, bilayer thickness (DHH), lateral diffusion, order parameter (P2), bending rigidity (kc), intermolecular and intramolecular splay angles, and curvature-driven lipid sorting. Results show that (1) M3 agrees more closely with C36 than M2 for most structural and mechanical properties; (2) strong correlations exist between order, rigidity, and splay across models, with nuanced differences revealing insights into local-to-global mechanical coupling; (3) C36 exhibits markedly stronger cholesterol-induced rigidification in complex mixtures than either coarse-grained (CG) model; (4) buckling reduces order and increases splay, with CG models, especially M2, better accommodating large deformations due to inherent softness; and (5) lipid sorting in buckled PM8 shows conserved trends, such as phosphatidylethanolamine enrichment in high-curvature regions, alongside force-field-specific differences, such as PIP2 clustering. These findings provide practical guidance for force field selection, inform ongoing CG parameterization efforts, and yield mechanistic insights into curvature sensing and sorting relevant to biological membrane function.
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