Systematic Methods for Structurally Consistent Coarse-Grained Models

Noid, W. G.

doi:10.1007/978-1-62703-017-5_19

Cited by 77 publications

(85 citation statements)

References 181 publications

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“…[9][10][11][12] Irrespective of the resolution, many force-field parametrization methodologies aim at reproducing target properties of an underlying microscopic model. These might be thermodynamic data from bulk systems (such as pure-liquid density and heat of vaporization for atomistic models 13 ), or local interaction statistics (such as structure factors or pair forces 14 ). While they can help reproduce a number of thermodynamic properties, the model's transferability across both thermodynamic parameters (e.g., temperature, pressure) and environments (e.g., bulk vs. interface) often remains of concern.…”

Section: Introductionmentioning

confidence: 99%

More than the sum of its parts: Coarse-grained peptide-lipid interactions from a simple cross-parametrization

Bereau

Wang

Deserno

2014

The Journal of Chemical Physics

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Interfacial systems are at the core of fascinating phenomena in many disciplines, such as biochemistry, soft-matter physics, and food science. However, the parametrization of accurate, reliable, and consistent coarse-grained (CG) models for systems at interfaces remains a challenging endeavor. In the present work, we explore to what extent two independently developed solvent-free CG models of peptides and lipids-of different mapping schemes, parametrization methods, target functions, and validation criteria-can be combined by only tuning the cross-interactions. Our results show that the cross-parametrization can reproduce a number of structural properties of membrane peptides (for example, tilt and hydrophobic mismatch), in agreement with existing peptide-lipid CG force fields. We find encouraging results for two challenging biophysical problems: (i) membrane pore formation mediated by the cooperative action of several antimicrobial peptides, and (ii) the insertion and folding of the helix-forming peptide WALP23 in the membrane. © 2014 AIP Publishing LLC.

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Section: Introductionmentioning

confidence: 99%

More than the sum of its parts: Coarse-grained peptide-lipid interactions from a simple cross-parametrization

Bereau

Wang

Deserno

2014

The Journal of Chemical Physics

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“…The numerical implementation of this variational principle works in such a way that the exact many-body PMF (Equation (6)) is represented by a linear combination of basis functions that are functions of the CG site coordinates [14,15]. For a given configuration of the CG coordinates, in fact, the average of the total atomistic force f α acting on a CG site α is equal to the derivative of the many-body PMF:…”

Section: The Mapping Function and The Potential Of Mean Forcementioning

confidence: 99%

“…The force-matching strategy thus projects the true many-body PMF onto the basis of functions that are used to define the CG force-field; a thorough formal explanation of this interpretation can be found in Reference [14,15].…”

Section: The Mapping Function and The Potential Of Mean Forcementioning

confidence: 99%

“…In order to overcome this limitation, coarse-grained models [10][11][12][13][14][15] have been developed, where the structure and interactions of the original system are replaced with simpler ones, which are easier to describe, model, simulate and understand. The assumption underlying the coarse-graining of a system is that above a given length scale the low-level, chemistry-specific detail of the model affects some properties of the system only in a simple, functionally trivial way -often through prefactors.…”

Section: Introductionmentioning

confidence: 99%

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Computer Simulations of Soft Matter: Linking the Scales

Potestio

Peter

Kremer

2014

Entropy

102

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Abstract:In the last few decades, computer simulations have become a fundamental tool in the field of soft matter science, allowing researchers to investigate the properties of a large variety of systems. Nonetheless, even the most powerful computational resources presently available are, in general, sufficient to simulate complex biomolecules only for a few nanoseconds. This limitation is often circumvented by using coarse-grained models, in which only a subset of the system's degrees of freedom is retained; for an effective and insightful use of these simplified models; however, an appropriate parametrization of the interactions is of fundamental importance. Additionally, in many cases the removal of fine-grained details in a specific, small region of the system would destroy relevant features; such cases can be treated using dual-resolution simulation methods, where a subregion of the system is described with high resolution, and a coarse-grained representation is employed in the rest of the simulation domain. In this review we discuss the basic notions of coarse-graining theory, presenting the most common methodologies employed to build low-resolution descriptions of a system and putting particular emphasis on their similarities and differences. The AdResS and H-AdResS adaptive resolution simulation schemes are reported as examples of dual-resolution approaches, especially focusing in particular on their theoretical background.

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“…Simulations based on coarse-grained models can access longer time and length scales than their atomistic counterparts, allowing a bulk description of fluids. Coarse-grained models are commonly used to represent a simplified picture of large molecules, such as biomolecules [12][13][14][15][16], polymers [17][18][19][20][21][22], or liquid crystals [23][24][25][26][27][28]. Moreover, simulation results obtained from coarse-grained models can be directly compared with theoretical predictions that are based on a well-defined Hamiltonian, such as the family of perturbation theories developed from the statistical association fluid theory (SAFT) [29][30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Liquid-crystal phase equilibria of Lennard-Jones chains

2016

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Liquid-crystal phase equilibria of Lennard-Jones chain fluids and the solubility of a Lennard-Jones gas in the coexisting phases are calculated from Monte Carlo simulations. Direct phase equilibria calculations are performed using an expanded formulation of the Gibbs ensemble. Monomer densities, order parameters, and equilibrium pressures are reported for the coexisting isotropic and nematic phases of: (1) linear Lennard-Jones chains, (2) a partially-flexible Lennard-Jones chain, and (3) a binary mixture of linear Lennard-Jones chains. The effect of chain length is determined by calculating the isotropic-nematic coexistence of linear Lennard-Jones chain fluids made of 8, 10, and 12 segments (8-, 10-, 12-mer). The effect of molecular flexibility on the isotropic-nematic equilibrium is studied for a Lennard-Jones 10-mer chain fluid with one freely-jointed segment at the end of the chain. An isotropic-nematic phase split and fractionation are reported for a binary mixture of linear 7-mer and 12-mer chains. Simulation results are compared with theoretical results as obtained from a recently developed analytical equation of state based on perturbation theory. Excellent agreement between theory and simulations is observed. The solubility of a monomer Lennard-Jones gas in the coexisting isotropic and nematic phases is estimated using the Widom test-particle insertion method. A linear relationship between solubility difference and density difference at isotropic-nematic coexistence is observed. It is shown that gas solubility is independent of the nematic ordering of the fluid, at constant temperature and density conditions.

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Systematic Methods for Structurally Consistent Coarse-Grained Models

Cited by 77 publications

References 181 publications

More than the sum of its parts: Coarse-grained peptide-lipid interactions from a simple cross-parametrization

More than the sum of its parts: Coarse-grained peptide-lipid interactions from a simple cross-parametrization

Computer Simulations of Soft Matter: Linking the Scales

Liquid-crystal phase equilibria of Lennard-Jones chains

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