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

2017Journal article Restricted access
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dc.contributor.authorSimões, Tiago M. C.
dc.contributor.authorLopes, Daniel Simões
dc.contributor.authorDias, Sérgio Emanuel Duarte
dc.contributor.authorFernandes, Francisco
dc.contributor.authorJorge, Joaquim A
dc.contributor.authorPereira, João
dc.contributor.authorBajaj, Chandrajit
dc.contributor.authorGomes, Abel
dc.date.accessioned2020-01-15T11:21:42Z
dc.date.available2020-01-15T11:21:42Z
dc.date.issued2017
dc.description.abstractDetecting and analysing protein cavities provides significant information about active sites for biological processes (e.g. protein–protein or protein–ligand binding) in molecular graphics and modelling. Using the three‐dimensional (3D) structure of a given protein (i.e. atom types and their locations in 3D) as retrieved from a PDB (Protein Data Bank) file, it is now computationally viable to determine a description of these cavities. Such cavities correspond to pockets, clefts, invaginations, voids, tunnels, channels and grooves on the surface of a given protein. In this work, we survey the literature on protein cavity computation and classify algorithmic approaches into three categories: evolution‐based, energy‐based and geometry‐based. Our survey focuses on geometric algorithms, whose taxonomy is extended to include not only sphere‐, grid‐ and tessellation‐based methods, but also surface‐based, hybrid geometric, consensus and time‐varying methods. Finally, we detail those techniques that have been customized for GPU (graphics processing unit) computing.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citation2017-Simoespt_PT
dc.identifier.doi10.1111/cgf.13158pt_PT
dc.identifier.eissn1467-8659
dc.identifier.urihttp://hdl.handle.net/10400.6/8303
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherJohn Wiley and Sonspt_PT
dc.relation.publisherversionhttps://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.13158pt_PT
dc.subjectProtein cavity detectionpt_PT
dc.subjectGeometric detection of protein pocketspt_PT
dc.subjectProtein cavitypt_PT
dc.subjectProtein pocketpt_PT
dc.titleGeometric Detection Algorithms for Cavities on Protein Surfaces in Molecular Graphics: A Surveypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage683pt_PT
oaire.citation.issue8pt_PT
oaire.citation.startPage643pt_PT
oaire.citation.titleComputer Graphics Forumpt_PT
oaire.citation.volume36pt_PT
person.familyNameSimões
person.familyNameDias
person.familyNameJorge
person.familyNameBajaj
person.familyNamePadrão Gomes
person.givenNameTiago Miguel Carrola
person.givenNameSérgio
person.givenNameJoaquim
person.givenNameChandrajit
person.givenNameAbel João
person.identifiervVp4XfYAAAAJ&hl
person.identifierJ-8234-2017
person.identifierH-9602-2014
person.identifier.ciencia-idFA1F-AB0F-45A4
person.identifier.ciencia-id0512-AF85-D322
person.identifier.ciencia-id0912-2821-9E60
person.identifier.ciencia-idEC1D-4ACD-6A62
person.identifier.orcid0000-0001-8858-0027
person.identifier.orcid0000-0002-9752-9386
person.identifier.orcid0000-0001-5441-4637
person.identifier.orcid0000-0002-9619-3278
person.identifier.orcid0000-0002-5804-5717
person.identifier.ridC-5596-2008
person.identifier.scopus-author-id36668366300
person.identifier.scopus-author-id36882820600
person.identifier.scopus-author-id8325080300
rcaap.embargofctEste artigo foi publicado em regime de acesso fechado.pt_PT
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublicationd2fc9f99-653f-4cf9-a887-6e83006abb45
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relation.isAuthorOfPublicationf3343549-f3b7-4eb3-a67c-e3bea4c8358e
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