GPU-Based De- tection of Protein Cavities using Gaussian Surfaces

Detalhes bibliográficos
Autor(a) principal: Dias, Sérgio
Data de Publicação: 2017
Outros Autores: Martins, Ana Mafalda, Nguyen, Quoc, Gomes, Abel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.6/8304
Resumo: Protein cavities play a key role in biomolecular recognition and function, particularly in protein-ligand interactions, as usual in drug discovery and design. Grid-based cavity detection methods aim at finding cavities as aggregates of grid nodes outside the molecule, under the condition that such cavities are bracketed by nodes on the molecule surface along a set of directions (not necessarily aligned with coordinate axes). Therefore, these methods are sensitive to scanning directions, a problem that we call cavity ground-and-walls ambiguity, i.e., they depend on the position and orientation of the protein in the discretized domain. Also, it is hard to distinguish grid nodes belonging to protein cavities amongst all those outside the protein, a problem that we call cavity ceiling ambiguity.
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spelling GPU-Based De- tection of Protein Cavities using Gaussian SurfacesProtein cavityProtein pocketGeometric detection of pocketsGPU computingProtein cavities play a key role in biomolecular recognition and function, particularly in protein-ligand interactions, as usual in drug discovery and design. Grid-based cavity detection methods aim at finding cavities as aggregates of grid nodes outside the molecule, under the condition that such cavities are bracketed by nodes on the molecule surface along a set of directions (not necessarily aligned with coordinate axes). Therefore, these methods are sensitive to scanning directions, a problem that we call cavity ground-and-walls ambiguity, i.e., they depend on the position and orientation of the protein in the discretized domain. Also, it is hard to distinguish grid nodes belonging to protein cavities amongst all those outside the protein, a problem that we call cavity ceiling ambiguity.BMCuBibliorumDias, SérgioMartins, Ana MafaldaNguyen, QuocGomes, Abel2020-01-15T11:27:10Z20172017-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.6/8304eng2017-Dias1471-210510.1186/s12859-017-1913-4info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-12-15T09:48:14Zoai:ubibliorum.ubi.pt:10400.6/8304Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:48:40.054305Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
title GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
spellingShingle GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
Dias, Sérgio
Protein cavity
Protein pocket
Geometric detection of pockets
GPU computing
title_short GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
title_full GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
title_fullStr GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
title_full_unstemmed GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
title_sort GPU-Based De- tection of Protein Cavities using Gaussian Surfaces
author Dias, Sérgio
author_facet Dias, Sérgio
Martins, Ana Mafalda
Nguyen, Quoc
Gomes, Abel
author_role author
author2 Martins, Ana Mafalda
Nguyen, Quoc
Gomes, Abel
author2_role author
author
author
dc.contributor.none.fl_str_mv uBibliorum
dc.contributor.author.fl_str_mv Dias, Sérgio
Martins, Ana Mafalda
Nguyen, Quoc
Gomes, Abel
dc.subject.por.fl_str_mv Protein cavity
Protein pocket
Geometric detection of pockets
GPU computing
topic Protein cavity
Protein pocket
Geometric detection of pockets
GPU computing
description Protein cavities play a key role in biomolecular recognition and function, particularly in protein-ligand interactions, as usual in drug discovery and design. Grid-based cavity detection methods aim at finding cavities as aggregates of grid nodes outside the molecule, under the condition that such cavities are bracketed by nodes on the molecule surface along a set of directions (not necessarily aligned with coordinate axes). Therefore, these methods are sensitive to scanning directions, a problem that we call cavity ground-and-walls ambiguity, i.e., they depend on the position and orientation of the protein in the discretized domain. Also, it is hard to distinguish grid nodes belonging to protein cavities amongst all those outside the protein, a problem that we call cavity ceiling ambiguity.
publishDate 2017
dc.date.none.fl_str_mv 2017
2017-01-01T00:00:00Z
2020-01-15T11:27:10Z
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url http://hdl.handle.net/10400.6/8304
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2017-Dias
1471-2105
10.1186/s12859-017-1913-4
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repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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