Dataset Information

Toward Hydrodynamics with Solvent Free Lipid Models: STRD Martini.

ABSTRACT: Solvent hydrodynamics are incorporated into simulations of the solvent-free Dry Martini model. The solvent hydrodynamics are modeled with the stochastic rotation dynamics (SRD) algorithm, a particle-based method for resolving fluid hydrodynamics. SRD does not require calculation of particle-particle distances in the solvent, and so is scalable to arbitrary volumes of solvent with minimal additional computational overhead. The viscosity of the solvent is easily tuned via parameters of the algorithm to span an order of magnitude in viscosity around the viscosity of water at room temperature. The combination "Stochastic Thermostatted Rotation Dynamics (STRD) with Martini" was implemented in Gromacs v.5.01. Simulations of an SRD/palmitoyloleoylphosphatidylcholine membrane demonstrate that the solvent may be included without reparametrizing the lipid model, with minimal perturbation to the thermodynamics. A recent generalization of Saffman-Delbruck theory to periodic geometries by Camley and Brown indicates that lipid dynamics are contaminated by a finite-size effect in typical molecular dynamics (MD) simulations, and that very large systems are required for quantitative simulation of dynamics. Analysis of lipid translational diffusion in this work shows good agreement with the theory, and with explicitly solvated simulations. This indicates that STRD Martini is a viable approach for quantitative simulation of membrane dynamics and does not require massive computational overhead to model the solvent.

SUBMITTER: Zgorski A

PROVIDER: S-EPMC5192689 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Toward Hydrodynamics with Solvent Free Lipid Models: STRD Martini.

Zgorski Andrew A Lyman Edward E

Biophysical journal 20161201 12

Solvent hydrodynamics are incorporated into simulations of the solvent-free Dry Martini model. The solvent hydrodynamics are modeled with the stochastic rotation dynamics (SRD) algorithm, a particle-based method for resolving fluid hydrodynamics. SRD does not require calculation of particle-particle distances in the solvent, and so is scalable to arbitrary volumes of solvent with minimal additional computational overhead. The viscosity of the solvent is easily tuned via parameters of the algorit ...[more]

PMID: 28002745

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Project description:After two decades of continued development of the Martini coarse-grained force field (CG FF), further refinment of the already rather accurate Martini lipid models has become a demanding task that could benefit from integrative data-driven methods. Automatic approaches are increasingly used in the development of accurate molecular models, but they typically make use of specifically designed interaction potentials that transfer poorly to molecular systems or conditions different than those used for model calibration. As a proof of concept, here, we employ SwarmCG, an automatic multiobjective optimization approach facilitating the development of lipid force fields, to refine specifically the bonded interaction parameters in building blocks of lipid models within the framework of the general Martini CG FF. As targets of the optimization procedure, we employ both experimental observables (top-down references: area per lipid and bilayer thickness) and all-atom molecular dynamics simulations (bottom-up reference), which respectively inform on the supra-molecular structure of the lipid bilayer systems and on their submolecular dynamics. In our training sets, we simulate at different temperatures in the liquid and gel phases up to 11 homogeneous lamellar bilayers composed of phosphatidylcholine lipids spanning various tail lengths and degrees of (un)saturation. We explore different CG representations of the molecules and evaluate improvements a posteriori using additional simulation temperatures and a portion of the phase diagram of a DOPC/DPPC mixture. Successfully optimizing up to ∼80 model parameters within still limited computational budgets, we show that this protocol allows the obtainment of improved transferable Martini lipid models. In particular, the results of this study demonstrate how a fine-tuning of the representation and parameters of the models may improve their accuracy and how automatic approaches, such as SwarmCG, may be very useful to this end.

Dataset Information

Toward Hydrodynamics with Solvent Free Lipid Models: STRD Martini.

Publications

Toward Hydrodynamics with Solvent Free Lipid Models: STRD Martini.

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