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dc.contributor.authorXu, Dong
dc.contributor.authorZhang, Yang
dc.date.accessioned2014-03-14T19:52:20Z
dc.date.available2014-03-14T19:52:20Z
dc.date.issued2009-12-02
dc.identifier.citationXu, D., & Zhang, Y. (2009). Generating Triangulated Macromolecular Surfaces by Euclidean Distance Transform. PLoS ONE, 4(12). http://dx.doi.org/10.1371/journal.pone.0008140
dc.identifier.urihttp://hdl.handle.net/1808/13173
dc.description.abstractMacromolecular surfaces are fundamental representations of their three-dimensional geometric shape. Accurate calculation of protein surfaces is of critical importance in the protein structural and functional studies including ligand-protein docking and virtual screening. In contrast to analytical or parametric representation of macromolecular surfaces, triangulated mesh surfaces have been proved to be easy to describe, visualize and manipulate by computer programs. Here, we develop a new algorithm of EDTSurf for generating three major macromolecular surfaces of van der Waals surface, solvent-accessible surface and molecular surface, using the technique of fast Euclidean Distance Transform (EDT). The triangulated surfaces are constructed directly from volumetric solids by a Vertex-Connected Marching Cube algorithm that forms triangles from grid points. Compared to the analytical result, the relative error of the surface calculations by EDTSurf is <2–4% depending on the grid resolution, which is 1.5–4 times lower than the methods in the literature; and yet, the algorithm is faster and costs less computer memory than the comparative methods. The improvements in both accuracy and speed of the macromolecular surface determination should make EDTSurf a useful tool for the detailed study of protein docking and structure predictions. Both source code and the executable program of EDTSurf are freely available at http://zhang.bioinformatics.ku.edu/EDTSu​rf.
dc.description.sponsorshipFunding: The project is supported by the Alfred P. Sloan Foundation, NSF Career Award 0746198 and the National Institute of General Medical Sciences Grant GM083107 and GM084222. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
dc.publisherPublic Library of Science
dc.rightsCopyright: ©2009 Xu, Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAlgorithms
dc.subjectComputing methods
dc.subjectMacromolecules
dc.subjectMolecular Computing
dc.subjectMolecular Structure
dc.subjectProtein structure
dc.subjectProtein Structure Prediciton
dc.subjectRadii
dc.titleGenerating Triangulated Macromolecular Surfaces by Euclidean Distance Transform
dc.typeArticle
kusw.kuauthorXu, Dong
kusw.kuauthorZhang, Yang
kusw.kudepartmentMolecular Biosciences
kusw.kudepartmentBioinformatics
kusw.oastatusfullparticipation
dc.identifier.doi10.1371/journal.pone.0008140
kusw.oaversionScholarly/refereed, publisher version
kusw.oapolicyThis item meets KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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Copyright: ©2009 Xu, Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Except where otherwise noted, this item's license is described as: Copyright: ©2009 Xu, Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited