Literature DB >> 26356962

Ligand Excluded Surface: A New Type of Molecular Surface.

Norbert Lindow, Daniel Baum, Hans-Christian Hege.   

Abstract

The most popular molecular surface in molecular visualization is the solvent excluded surface (SES). It provides information about the accessibility of a biomolecule for a solvent molecule that is geometrically approximated by a sphere. During a period of almost four decades, the SES has served for many purposes - including visualization, analysis of molecular interactions and the study of cavities in molecular structures. However, if one is interested in the surface that is accessible to a molecule whose shape differs significantly from a sphere, a different concept is necessary. To address this problem, we generalize the definition of the SES by replacing the probe sphere with the full geometry of the ligand defined by the arrangement of its van der Waals spheres. We call the new surface ligand excluded surface (LES) and present an efficient, grid-based algorithm for its computation. Furthermore, we show that this algorithm can also be used to compute molecular cavities that could host the ligand molecule. We provide a detailed description of its implementation on CPU and GPU. Furthermore, we present a performance and convergence analysis and compare the LES for several molecules, using as ligands either water or small organic molecules.

Entities:  

Year:  2014        PMID: 26356962     DOI: 10.1109/TVCG.2014.2346404

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  2 in total

1.  Geometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Survey.

Authors:  Tiago Simões; Daniel Lopes; Sérgio Dias; Francisco Fernandes; João Pereira; Joaquim Jorge; Chandrajit Bajaj; Abel Gomes
Journal:  Comput Graph Forum       Date:  2017-06-01       Impact factor: 2.078

2.  Ellipsoidal Abstract and Illustrative Representations of Molecular Surfaces.

Authors:  Meng Liang; Yuhang Fu; Ruibo Gao; Qiaoqiao Wang; Junlan Nie
Journal:  Int J Mol Sci       Date:  2019-10-17       Impact factor: 5.923

  2 in total

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