The MARTINI Coarse-Grained Force Field: Extension to Proteins

190

198

Hybrid simulations, in which part of the system is represented at atomic resolution and the remaining part at a reduced, coarse-grained, level offer a powerful way to combine the accuracy associated with the atomistic force fields to the sampling speed obtained with coarse-grained (CG) potentials. In this work we introduce a straightforward scheme to perform hybrid simulations, making use of virtual sites to couple the two levels of resolution. With the help of these virtual sites interactions between molecules at different levels of resolution, i.e. between CG and atomistic molecules, are treated the same way as the pure CG-CG interactions. To test our method, we combine the Gromos atomistic force field with a number of coarse-grained potentials, obtained through several approaches that are designed to obtain CG potentials based on an existing atomistic model, namely iterative Boltzmann inversion, force matching, and a potential of mean force subtraction procedure (SB). We also explore the use of the MARTINI force field for the CG potential. A simple system, consisting of atomistic butane molecules dissolved in CG butane, is used to study the performance of our hybrid scheme. Based on the potentials of mean force for atomistic butane in CG solvent, and the properties of 1 : 1 mixtures of atomistic and CG butane which should exhibit ideal mixing behavior, we conclude that the MARTINI and SB potentials are particularly suited to be combined with the atomistic force field. The MARTINI potential is subsequently used to perform hybrid simulations of atomistic dialanine peptides in both CG butane and water. Compared to a fully atomistic description of the system, the hybrid description gives similar results provided that the dielectric screening of water is accounted for. Within the field of biomolecules, our method appears ideally suited to study e.g. protein-ligand binding, where the active site and ligand are modeled in atomistic detail and the rest of the protein, together with the solvent, is coarse-grained.

Section: Discussionmentioning

confidence: 99%

Section: Coarse Grained Potentialsmentioning

confidence: 99%

Hybrid simulations: combining atomistic and coarse-grained force fields using virtual sites

Rzepiela

Louhivuori

Peter

et al. 2011

190

198

“…This is the method used, for example, in the case of DPD or the MARTINI model. [18][19][20] It is, however, also possible to derive the interaction potentials in a systematic fashion, and this is what we will be discussing in the this section. Several of the methods that achieve this rely on what is known as the Henderson theorem, to be derived in section IIA.…”

Section: Using Structural Information: Iterative Methods and Densmentioning

confidence: 99%

Multiscale modeling of emergent materials: biological and soft matter

Murtola

Bunker

Vattulainen

et al. 2009

260

234

On using a too large integration time step in molecular dynamics simulations of coarse-grained molecular models Moritz Winger, Daniel Trzesniak, Riccardo Baron and Wilfred F. In this review, we focus on four current related issues in multiscale modeling of soft and biological matter. First, we discuss how to use structural information from detailed models (or experiments) to construct coarse-grained ones in a hierarchical and systematic way. This is discussed in the context of the so-called Henderson theorem and the inverse Monte Carlo method of Lyubartsev and Laaksonen. In the second part, we take a different look at coarse graining by analyzing conformations of molecules. This is done by the application of self-organizing maps, i.e., a neural network type approach. Such an approach can be used to guide the selection of the relevant degrees of freedom. Then, we discuss technical issues related to the popular dissipative particle dynamics (DPD) method. Importantly, the potentials derived using the inverse Monte Carlo method can be used together with the DPD thermostat. In the final part we focus on solvent-free modeling which offers a different route to coarse graining by integrating out the degrees of freedom associated with solvent.

“…Coarse grain molecular dynamics simulations were performed using the GROMACS software package, version 4.5.5, 59 with the scheme developed for the MARTINI model. 55,56 The temperature was coupled (coupling time 0.1 ps) to an external heat bath at temperature T = 310 K or 325 K, using a Berendsen thermostat. 60 The time step of the simulation was 20 fs.…”

Section: Dimerization Profile Calculationsmentioning

confidence: 99%

Thermodynamic and kinetic characterization of transmembrane helix association

Pawar

Deshpande

Gopal

et al. 2015

The transient dimerization of transmembrane proteins is an important event in several cellular processes and computational methods are being increasingly used to quantify their underlying energetics. Here, we probe the thermodynamics and kinetics of a simple transmembrane dimer to understand membrane protein association. A multi-step framework has been developed in which the dimerization profiles are calculated from coarse-grain molecular dynamics simulations, followed by meso-scale simulations using parameters calculated from the coarse-grain model. The calculated value of DG assoc is approx. À20 kJ mol À1 and is consistent between three methods. Interestingly, the meso-scale stochastic model reveals low dimer percentages at physiologically-relevant concentrations, despite a favorable DG assoc . We identify generic driving forces arising from the protein backbone and lipid bilayer and complementary factors, such as protein density, that govern self-interactions in membranes. Our results provide an important contribution in understanding membrane protein organization and linking molecular, nano-scale computational studies to meso-scale experimental data.