Molecular Dynamics

Leimkuhler, Benedict; Matthews, Charles E.

doi:10.1007/978-3-319-16375-8

Cited by 168 publications

(78 citation statements)

References 292 publications

(457 reference statements)

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“…Significant results were summarized in [16]; in particular, attention was made to integration schemes that are suitable for particle dynamics. Later, particle system dynamics is segregated into several areas with designated set of models -molecular dynamics, dynamics of complex and non-Newtonian fluids, smoothed particle hydrodynamics and more [17][18][19][20][21][22]. Representation in form of particle system has many advantages: simple underlying theory, natural representation of many building materials, ability to model arbitrary pair forces, possibility to investigate large and nonlinear deformations, crack propagation and contact interactions.…”

Section: Structural Levels Of Building Materialsmentioning

confidence: 99%

Multiscale material design in construction

2017

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Abstract. Classic R&D in material science was based on statistical modeling. However, large number of control factors and the absence of universal computational method that can be used for numerical investigation at all structural levels of constructional composite dictate the necessity of multiscale approach in computational material science. In the present work we are focusing on the description of spatial scales and primary types of interactions that take place in different layers of building materials. The five spatial scales are considered. Three of them allow using the simplest and universal modeling method that is based on the representation of composite as a particle system; still, modeling requires taking into account some extra types of pair forces and forces that are arising due to technological actions.

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Section: Structural Levels Of Building Materialsmentioning

confidence: 99%

Multiscale material design in construction

2017

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“…Significant results summarized in [9]; in particular, attention was made to integration schemes suitable for particle dynamics. During the course of elaboration, particle system dynamics is segregated into several areas with designated set of models -molecular dynamics (additional semiclassical provisions from quantum physics), dynamics of complex and non-Newtonian fluids, smoothed particle hydrodynamics and more [7][8][9][10][11].…”

Section: Particle System Dynamicsmentioning

confidence: 99%

“…As it can be concluded from previous brief review and relevant works [7,9,11,12] in the field, solution of set of ordinary differential equations (ODE) is the essence of any particle system dynamics software. The model is based on classical mechanics; this model includes potential (force field) representing pairwise interaction.…”

Section: Particle System Softwarementioning

confidence: 99%

“…The current key features of the LAMMPS are similar to ones of the GROMACS; in particular, great attention was paid to the special-purpose parallelization algorithms [21,22]. It is also stated that LAMMPS was originally designed for materials applications and offers a convenient mechanism for code modification [11].…”

Section: Available Open Source Software Packages For Particle System mentioning

confidence: 99%

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Particle System Dynamics Software for the Design of Constructional Composites

2015

2015 International Conference on Data Mining, Electronics and Information Technology (DMEIT'15) August 10-11, 2015 Pattaya, Tha

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“…We neglect this bias, since the specific integrator employed here is thought to preserve the configurational distribution to very high accuracy . 47,48 This conclusion is based on analytical results showing that the integrator approximates configurational averages to fourthorder in the timestep (as opposed to second-order for competing integrators), and extensive numerical evidence examining particular biomolecular observ-ables. 47,48 Further, it has been argued more generically that the contribution of "shadow work" in nonequilibrium simulations can be neglected without introducing much bias.…”

Section: Nonequilibrium Candidate Monte Carlo (Ncmc) Couples MD With mentioning

confidence: 99%

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

Gill¹,

Lim²,

Grinaway³

et al. 2017

Preprint

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Accurately predicting protein-ligand binding is a major goal in computational chemistry, but even the prediction of ligand binding modes in proteins poses major challenges. Here, we focus on solving the binding mode prediction problem for rigid fragments. That is, we focus on computing the dominant placement, conformation, and orientations of a relatively rigid, fragment-like ligand in a receptor, and the populations of the multiple binding modes which may be relevant. This problem is important in its own right, but is even more timely given the recent success of alchemical free energy calculations. Alchemical calculations are increasingly used to predict binding free energies of ligands to receptors. However, the accuracy of these calculations is dependent on proper sampling of the relevant ligand binding modes. Unfortunately, ligand binding modes may often be uncertain, hard to predict, and/or slow to interconvert on simulation timescales, so proper sampling with current techniques can require prohibitively long simulations. We need new methods which dramatically improve sampling of ligand binding modes. Here, we develop and apply a nonequilibrium candidate Monte Carlo (NCMC) method to improve sampling of ligand binding modes. In this technique the ligand is rotated and subsequently allowed to relax in its new position through alchemical perturbation before accepting or rejecting the rotation and relaxation as a nonequilibrium Monte Carlo move. When applied to a T4 lysozyme model binding system, this NCMC method shows over two orders of magnitude improvement in binding mode sampling efficiency compared to a brute force molecular dynamics simulation. This is a first step towards applying this methodology to pharmaceutically-relevant binding of fragments and, eventually, drug-like molecules. We are making this approach available via our new Binding Modes of Ligands using Enhanced Sampling (BLUES) package which is freely available on GitHub.

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Molecular Dynamics

Cited by 168 publications

References 292 publications

Multiscale material design in construction

Multiscale material design in construction

Particle System Dynamics Software for the Design of Constructional Composites

Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes Using Nonequilibrium Candidate Monte Carlo

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