Abstract

Water models with realistic physical–chemical properties are essential to study a variety of biomedical processes or engineering technologies involving molecules or nanomaterials. Atomistic models of water are constrained by the feasible computational capacity, but calibrated coarse-grained (CG) ones can go beyond these limits. Here, we compare three popular atomistic water models with their corresponding CG model built using finite-size particles such as ellipsoids. Differently from previous approaches, short-range interactions are accounted for with the generalized Gay–Berne potential, while electrostatic and long-range interactions are computed from virtual charges inside the ellipsoids. Such an approach leads to a quantitative agreement between the original atomistic models and their CG counterparts. Results show that a timestep of up to 10 fs can be achieved to integrate the equations of motion without significant degradation of the physical observables extracted from the computed trajectories, thus unlocking a significant acceleration of water-based mesoscopic simulations at a given accuracy.

Highlights

  • Coarse-grained (CG) molecular dynamics (MD) simulations offer an efficient way to study the most diverse systems at a mesoscopic scale, with applications ranging from biochemistry[1,2] to material science.[3−5] The basic idea behind CG is to decrease the number of interacting sites describing individual molecules

  • We test the validity of the MOLC representation for three widely used all-atom water models, namely, SPC-E,27 Tip3PEw,[28] and Tip4P-05,29 by comparing the computed selfdiffusion coefficient, dynamic viscosity, surface free energy, and enthalpy of vaporization[30−37] between the AA and corresponding CG models at T = 298 K and p = 1 atm

  • For the sake of simplicity, from this point on, we will refer to the Tip3P-Ew and Tip4P-05 models as Tip3P and Tip4P, respectively

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Summary

Introduction

Coarse-grained (CG) molecular dynamics (MD) simulations offer an efficient way to study the most diverse systems at a mesoscopic scale, with applications ranging from biochemistry[1,2] to material science.[3−5] The basic idea behind CG is to decrease the number of interacting sites describing individual molecules. By reducing the model resolution, the computational cost and the configuration space of the system decrease, enabling the modeling of larger and more complex systems compared to atomistic simulations. For some phenomena, such as the conformation change of enzymes and functional proteins,[6,7] the limiting factor of all-atom (AA) simulations is the timescale needed to witness a specific process. In this regard, CG models enable longer timesteps and accessible simulation times by suppressing the highfrequency motion characteristics of light atoms and/or averaging out some intramolecular degrees of freedom. From previous approaches, short-range interactions are accounted for with the generalized Gay−Berne potential,[15] while electrostatic and long-range interactions with a modified version of the usual Coulomb pairwise summation and the reciprocal-space Ewald solver, respectively.[16]

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