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Sphericity of a protein via the beta-complex

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dc.contributor.authorKim, Deok-Soo-
dc.contributor.authorKim, Jae-Kwan-
dc.contributor.authorWon, Chung-In-
dc.contributor.authorKim, Chong-Min-
dc.contributor.authorPark, Joon Young-
dc.contributor.authorBhak, Jong-
dc.date.accessioned2022-12-20T18:16:19Z-
dc.date.available2022-12-20T18:16:19Z-
dc.date.created2022-08-27-
dc.date.issued2010-04-
dc.identifier.issn1093-3263-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/175174-
dc.description.abstractMolecular shape is a fundamental factor in determining the function of a molecule. As proteins tend to fold into globular shapes, the shape descriptor for protein sphericity is important in understanding molecular functions. In this paper, a definition of protein sphericity is introduced based on the recently developed geometric constructs of the beta-complex and beta-shape of a protein. The beta-complex represents the Euclidean proximity among all the atoms in a protein, and the beta-shape is the polyhedron contained within the boundary of the corresponding beta-complex. Hence, the beta-shape determines the proximity among the atoms on the boundary of a protein. Given the volume of a beta-shape, the ratio between the surface area of a sphere with this volume and the surface area of the beta-shape itself is a good measure to classify the sphericity of a protein, especially when the radius of a probe is 3.0 angstrom. The presented measure is invariant to translation and rotation.-
dc.language영어-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE INC-
dc.titleSphericity of a protein via the beta-complex-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Deok-Soo-
dc.identifier.doi10.1016/j.jmgm.2010.01.001-
dc.identifier.scopusid2-s2.0-76549089189-
dc.identifier.wosid000276287200006-
dc.identifier.bibliographicCitationJOURNAL OF MOLECULAR GRAPHICS & MODELLING, v.28, no.7, pp.636 - 649-
dc.relation.isPartOfJOURNAL OF MOLECULAR GRAPHICS & MODELLING-
dc.citation.titleJOURNAL OF MOLECULAR GRAPHICS & MODELLING-
dc.citation.volume28-
dc.citation.number7-
dc.citation.startPage636-
dc.citation.endPage649-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaCrystallography-
dc.relation.journalResearchAreaMathematical & Computational Biology-
dc.relation.journalWebOfScienceCategoryBiochemical Research Methods-
dc.relation.journalWebOfScienceCategoryBiochemistry & Molecular Biology-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryCrystallography-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.subject.keywordPlusVORONOI-DIAGRAM-
dc.subject.keywordPlusSURFACE-AREA-
dc.subject.keywordPlusMOLECULAR-SURFACES-
dc.subject.keywordPlusEXCLUDED-VOLUME-
dc.subject.keywordPlusCIRCLE SET-
dc.subject.keywordPlusPOINT SET-
dc.subject.keywordPlusCOMPUTATION-
dc.subject.keywordPlusEFFICIENT-
dc.subject.keywordPlusSOLVENT-
dc.subject.keywordPlusSPHERES-
dc.subject.keywordAuthorProtein structure-
dc.subject.keywordAuthorSphericity-
dc.subject.keywordAuthorVoronoi diagram-
dc.subject.keywordAuthorbeta-complex-
dc.subject.keywordAuthorbeta-shape-
dc.subject.keywordAuthorPDB-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S1093326310000021?via%3Dihub-
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