Modification of the overlap potential to mimic a linear site–site potential

Gay, J. G.; Berne, B. J.

doi:10.1063/1.441483

Cited by 1,249 publications

(845 citation statements)

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“…14 Inevitably, the basic units of these programs are atoms displayed as spheres or as vertices in a wireframe or "neon tube" graph. However, the Gay-Berne family of anisotropic potentials employs soft ellipsoids as basic modeling units to represent whole rodlike 15 or platelike 16 (and thus usually mesogenic) molecules, in order to speed up Monte Carlo and molecular dynamics 17 calculations by giving up intramolecular detail. Other popular choices for the same purpose are soft spherocylinders; 18 soft biaxial ellipsoids, 19 hard ellipsoids and spherocylinders, 20 and several other site-site variants 21 are employed too.…”

Section: Introductionmentioning

confidence: 99%

Molecular Graphics of Convex Body Fluids

Gabriel

Meyer

Germano

2008

J. Chem. Theory Comput.

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Coarse-grained modeling of molecular fluids is often based on nonspherical convex rigid bodies like ellipsoids or spherocylinders representing rodlike or platelike molecules or groups of atoms, with site-site interaction potentials depending both on the distance among the particles and the relative orientation. In this category of potentials, the Gay-Berne family has been studied most extensively. However, conventional molecular graphics programs are not designed to visualize such objects. Usually the basic units are atoms displayed as spheres or as vertices in a graph. Atomic aggregates can be highlighted through an increasing amount of stylized representations, e.g., Richardson ribbon diagrams for the secondary structure of proteins, Connolly molecular surfaces, density maps, etc., but ellipsoids and spherocylinders are generally missing, especially as elementary simulation units. We fill this gap providing and discussing a customized OpenGL-based program for the interactive, rendered representation of large ensembles of convex bodies, useful especially in liquid crystal research. We pay particular attention to the performance issues for typical system sizes in this field. The code is distributed as open source.

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Section: Introductionmentioning

confidence: 99%

Molecular Graphics of Convex Body Fluids

Gabriel

Meyer

Germano

2008

J. Chem. Theory Comput.

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“…Examples include orientation-dependent interaction potentials, which are widely used in mesoscopic simulations. [7][8][9][10][11][12] All the methodology presented has been implemented in our public domain programs GMIN 55 and OPTIM, 40 and in a python package. 56 When dealing with rigid bodies, there are two relevant frames of reference: the laboratory frame and the instantaneous frame.…”

Section: Discussionmentioning

confidence: 99%

“…8,31 In such cases, the gyration tensor is chosen directly to describe the shape of the underlying model.…”

Section: A Metric Tensor For Infinitesimal Distancesmentioning

confidence: 99%

“…5,6 For simulations on longer length scales, coarse-grained descriptions are typically used, which may involve orientation-dependent potentials to describe nonspherical molecules with convex shapes. [7][8][9][10][11][12] To represent an anisotropic molecule or interaction potential, six degrees of freedom are required (unless the molecule is linear): three for the translation of the center of mass, and three for the orientation. The treatment of translational degrees of freedom is straightforward: they are usually represented by orthogonal Cartesian coordinates.…”

Section: Introductionmentioning

confidence: 99%

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Exploring Energy Landscapes: Metrics, Pathways, and Normal-Mode Analysis for Rigid-Body Molecules

Rühle

Kusumaatmaja

Chakrabarti

et al. 2013

J. Chem. Theory Comput.

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We present new methodology for exploring the energy landscapes of molecular systems, using angle-axis variables for the rigid-body rotational coordinates. The key ingredient is a distance measure or metric tensor, which is invariant to global translation and rotation. The metric is used to formulate a generalized nudged elastic band method for calculating pathways, and a full prescription for normal-mode analysis is described. The methodology is tested by mapping the potential energy and free energy landscape of the water octamer, described by the TIP4P potential.

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“…156 The interaction sites are the united-atom side chains, and the centers of the peptide groups between C α atoms, which interact through empirical terms augmented by correlation terms (multiple-body interactions). The multiple-body interactions among peptide groups in the UNRES potential are represented in terms of a cumulant expansion of the free energy, 157 following Kubo, 158 and includes multibody cooperative terms whose relative weights are determined by a Z-score-and-gap optimization.…”

Section: Hierarchical Approach To the Prediction Of Protein Structurementioning

confidence: 99%

Evolution of physics‐based methodology for exploring the conformational energy landscape of proteins

Scheraga¹,

Pillardy²,

Liwo³

et al. 2001

J Comput Chem

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Abstract:The evolution of our physics-based computational methods for determining protein conformation without the introduction of secondary-structure predictions, homology modeling, threading, or fragment coupling is described. Initial use of a hard-sphere potential captured much of the structural properties of polypeptide chains, and subsequent more refined force fields, together with efficient methods of global optimization provide indications that progress is being made toward an understanding of the interresidue interactions that underlie protein folding.

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Modification of the overlap potential to mimic a linear site–site potential

Abstract: A modification of the overlap potential of Berne and Pechukas is proposed. The overlap strength and range parameters are used in a new functional form resulting in a single-site potential which closely resembles a linear site–site potential.

Cited by 1,249 publications

References 13 publications

Molecular Graphics of Convex Body Fluids

Molecular Graphics of Convex Body Fluids

Exploring Energy Landscapes: Metrics, Pathways, and Normal-Mode Analysis for Rigid-Body Molecules

Evolution of physics‐based methodology for exploring the conformational energy landscape of proteins

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