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CavBench: a benchmark for protein cavity detection methods

2019Journal article Open access
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dc.contributor.authorDias, Sérgio
dc.contributor.authorSimões, Tiago M. C.
dc.contributor.authorFernandes, Francisco
dc.contributor.authorMartins, Ana Mafalda
dc.contributor.authorFerreira, Alfredo
dc.contributor.authorJorge, Joaquim A
dc.contributor.authorGomes, Abel
dc.date.accessioned2020-01-14T17:10:00Z
dc.date.available2020-01-14T17:10:00Z
dc.date.issued2019
dc.description.abstractExtensive research has been applied to discover new techniques and methods to model protein-ligand interactions. In particular, considerable efforts focused on identifying candidate binding sites, which quite often are active sites that correspond to protein pockets or cavities. Thus, these cavities play an important role in molecular docking. However, there is no established benchmark to assess the accuracy of new cavity detection methods. In practice, each new technique is evaluated using a small set of proteins with known binding sites as ground-truth. However, studies supported by large datasets of known cavities and/or binding sites and statistical classification (i.e., false positives, false negatives, true positives, and true negatives) would yield much stronger and reliable assessments. To this end, we propose CavBench, a generic and extensible benchmark to compare different cavity detection methods relative to diverse ground truth datasets (e.g., PDBsum) using statistical classification methods.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citation2019-Simoespt_PT
dc.identifier.doi10.1371/journal.pone.0223596pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/8272
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherPLOSpt_PT
dc.relationInstituto de Telecomunicações
dc.relationInstituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa
dc.relationInteractive Tablets for Collaborative Scenarios Related to 3D Medical Image Exploration
dc.relationMorse Theory-Based Pockets Detection over Proteins and other Biomolecules
dc.relationEXPEDITIOUS MODELING FRAMEWORK FOR INTERACTIVE SKETCHING, SURFACE EDITING AND MANUFACTURING OF 3-D OBJECTS WITH APPLICATIONS IN TERRAIN MODELING AND RECONSTRUCTION OF BIOMEDICAL STRUCTURES
dc.relation.publisherversionhttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223596pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectProtein pocketpt_PT
dc.subjectProtein cavity detectionpt_PT
dc.titleCavBench: a benchmark for protein cavity detection methodspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleInstituto de Telecomunicações
oaire.awardTitleInstituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa
oaire.awardTitleInteractive Tablets for Collaborative Scenarios Related to 3D Medical Image Exploration
oaire.awardTitleMorse Theory-Based Pockets Detection over Proteins and other Biomolecules
oaire.awardTitleEXPEDITIOUS MODELING FRAMEWORK FOR INTERACTIVE SKETCHING, SURFACE EDITING AND MANUFACTURING OF 3-D OBJECTS WITH APPLICATIONS IN TERRAIN MODELING AND RECONSTRUCTION OF BIOMEDICAL STRUCTURES
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F50008%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FCEC%2F50021%2F2019/PT
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oaire.citation.endPage16pt_PT
oaire.citation.issue10pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titlePLoS ONEpt_PT
oaire.citation.volume14pt_PT
oaire.fundingStream6817 - DCRRNI ID
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oaire.fundingStream3599-PPCDT
person.familyNameDias
person.familyNameSimões
person.familyNameMartins
person.familyNameJorge
person.familyNamePadrão Gomes
person.givenNameSérgio
person.givenNameTiago Miguel Carrola
person.givenNameAna Mafalda
person.givenNameJoaquim
person.givenNameAbel João
person.identifierJ-8234-2017
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person.identifier.orcid0000-0002-7832-4430
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person.identifier.orcid0000-0002-5804-5717
person.identifier.ridC-5596-2008
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project.funder.identifierhttp://doi.org/10.13039/501100001871
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project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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rcaap.rightsopenAccesspt_PT
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