The Detailed Balance Energy-scaled Displacement Monte Carlo Algorithm

Mezei, Mihaly; Bencsáth, Katalin A.; Goldman, Saul; Singh, Shri

doi:10.1080/08927028708080933

Cited by 10 publications

(3 citation statements)

References 10 publications

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“…Not only intermolecular forces but also the virial in the NPT -ensemble can be included in the acceptance criterion to increase the sampling efficiency [ 51 ]. In addition, the step size of the attempted moves can be adjusted according to the total interaction energy of the particle [ 52 ]. Another way of accelerating equilibration of the system is to shift to the grand canonical ensemble (GCE) and to insert/delete molecules as part of the sampling procedure.…”

Section: Introductionmentioning

confidence: 99%

Atomistic Monte Carlo Simulation of Lipid Membranes

Wüstner

Sklenar

2014

IJMS

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Biological membranes are complex assemblies of many different molecules of which analysis demands a variety of experimental and computational approaches. In this article, we explain challenges and advantages of atomistic Monte Carlo (MC) simulation of lipid membranes. We provide an introduction into the various move sets that are implemented in current MC methods for efficient conformational sampling of lipids and other molecules. In the second part, we demonstrate for a concrete example, how an atomistic local-move set can be implemented for MC simulations of phospholipid monomers and bilayer patches. We use our recently devised chain breakage/closure (CBC) local move set in the bond-/torsion angle space with the constant-bond-length approximation (CBLA) for the phospholipid dipalmitoylphosphatidylcholine (DPPC). We demonstrate rapid conformational equilibration for a single DPPC molecule, as assessed by calculation of molecular energies and entropies. We also show transition from a crystalline-like to a fluid DPPC bilayer by the CBC local-move MC method, as indicated by the electron density profile, head group orientation, area per lipid, and whole-lipid displacements. We discuss the potential of local-move MC methods in combination with molecular dynamics simulations, for example, for studying multi-component lipid membranes containing cholesterol.

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Section: Introductionmentioning

confidence: 99%

Atomistic Monte Carlo Simulation of Lipid Membranes

Wüstner

Sklenar

2014

IJMS

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“…-6 < x < -3 and 3 < x < 6 -3 < x < 3 (10) We use the square root of the average fluctuation of ( ,/ ) to evaluate the convergence of ( ,? ) following m passes according to the method of Cao and Berne:5 position Figure 2.…”

Section: Ssm and The Free Energy Difference Methodsmentioning

confidence: 99%

The Subspace Sampling Method: A Monte Carlo Approach for Simulating the Single-Particle Density Function and the Equilibrium Constant for Systems Described by Multiple Hamiltonians

Shew¹,

Mills²

1995

J. Phys. Chem.

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We compute the single-particle density function and the equilibrium constant using the subspace sampling method (SSM) for three one-dimensional potentials. SSM is a versatile Monte Carlo methodology that partitions configuration space into subspaces. Such partitioning facilitates the sampling of regions of configuration space separated by potential barriers or described by different hamiltonians. We show that SSM can be readily used to compute simultaneously the density function and the equilibrium constant for the subspaces.Furthermore, alternative sampling schemes can be included in the SSM methodology to expedite Convergence. and minimize the need to search for an optimum parameter set.

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“…In a similar approach, attempted some time ago [14], the authors applied analytic functions r max (e k ) depending on the energy e k of the single particle k that is to be moved within a canonical ensemble. In contrast to the results presented here, decisive improvements could not be achieved.…”

Section: Displacement Move With Energy Dependent Maximal Step Lengthmentioning

confidence: 99%

Advanced multicanonical Monte Carlo methods for efficient simulations of nucleation processes of polymers

Schnabel¹,

Janke²,

Bachmann³

2011

Journal of Computational Physics

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a b s t r a c tThe investigation of freezing transitions of single polymers is computationally demanding, since surface effects dominate the nucleation process. In recent studies we have systematically shown that the freezing properties of flexible, elastic polymers depend on the precise chain length. Performing multicanonical Monte Carlo simulations, we faced several computational challenges in connection with liquid-solid and solid-solid transitions. For this reason, we developed novel methods and update strategies to overcome the arising problems. We introduce novel Monte Carlo moves and two extensions to the multicanonical method.

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The Detailed Balance Energy-scaled Displacement Monte Carlo Algorithm

Cited by 10 publications

References 10 publications

Atomistic Monte Carlo Simulation of Lipid Membranes

Atomistic Monte Carlo Simulation of Lipid Membranes

The Subspace Sampling Method: A Monte Carlo Approach for Simulating the Single-Particle Density Function and the Equilibrium Constant for Systems Described by Multiple Hamiltonians

Advanced multicanonical Monte Carlo methods for efficient simulations of nucleation processes of polymers

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