MesoMem: A mesoscale membrane model based on an additive potential

TL;DR

MesoMem is a new mesoscale membrane model that uses an additive potential to simulate biological membranes, capturing self-assembly, phase behavior, and remodeling with tunable mechanical properties.

Contribution

It introduces a solvent-free, coarse-grained membrane model with additive energy terms for tilt and splay, implemented in LAMMPS, enabling realistic membrane dynamics and remodeling simulations.

Findings

Spontaneous formation of lamellar structures and vesicles.

Reproduction of theoretical fluctuation spectra for tensionless membranes.

Demonstrated membrane remodeling via nanoparticle adhesion simulations.

Abstract

Bridging the gap between atomistic detail and continuum mechanics is a central challenge in modeling biological membranes, particularly for mesoscopic phenomena spanning large length and time scales. In this work, we introduce a new, solvent-free, one-particle-thick, coarse-grained model for lipid bilayers, governed by an additive potential. Our approach treats orientational elasticity through distinct additive energy terms for tilt and splay, offering an unbiased potential form. The model is implemented in the LAMMPS molecular dynamics engine. Our simulations show spontaneous self-assembly of lamellar structures and stable vesicles from disordered states. We map the dynamical phase diagram of the system, identifying distinct gel-like, fluid, and gas regimes, controlled by temperature and the steepness of the isotropic attraction. The model accurately reproduces the theoretical $1/q^{4}$ fluctuation spectrum for tensionless membranes and exhibits tunable mechanical properties, including biologically relevant bending rigidities and area compressibility moduli. We show how we can include osmotic pressure and spontaneous curvature in our model. Finally, we demonstrate the model's applicability to complex membrane remodeling by simulating the adhesive wrapping of colloidal nanoparticles, recovering the predicted dependency on particle size and adhesion strength.