Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1060954
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dc.contributor.authorBORRO, L.pt_BR
dc.contributor.authorYANO, I. H.pt_BR
dc.contributor.authorMAZONI, I.pt_BR
dc.contributor.authorNESHICH, G.pt_BR
dc.date.accessioned2017-01-17T11:11:11Zpt_BR
dc.date.available2017-01-17T11:11:11Zpt_BR
dc.date.created2017-01-17pt_BR
dc.date.issued2016pt_BR
dc.identifier.citationIn: STRUCTURAL BIOINFORMATICS AND COMPUTATIONAL BIOPHYSICS, 2016, Orlando. [Proceedings...]. Orlando: [s.n.], 2016.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1060954pt_BR
dc.descriptionWe propose a new empirical scoring function for binding affinity prediction modeled based on physicochemical and structural descriptors that characterize the nano-environment that encompass both ligand and binding pocket residues. Our hypothesis is that a more detailed characterization of protein-ligand complexes in terms of describing nano-environment as precisely as possible can lead to improvements in binding affinity prediction.pt_BR
dc.format1 pôster.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectInterações entre proteína e ligantespt_BR
dc.subjectModelagempt_BR
dc.subjectModelospt_BR
dc.subjectComplexo proteína-ligantept_BR
dc.subjectProtein-ligand complexpt_BR
dc.subjectBinding affinity prediction modelpt_BR
dc.subjectEmpiric nonparametric predictive modelpt_BR
dc.subjectPlataforma Stingpt_BR
dc.titleBinding affinity prediction using a nonparametric regression model based on physicochemical and structural descriptors of the nano-environment for protein-ligand interactions.pt_BR
dc.typeResumo em anais e proceedingspt_BR
dc.date.updated2020-01-21T11:11:11Zpt_BR
dc.subject.nalthesaurusBinding propertiespt_BR
dc.subject.nalthesaurusModelspt_BR
dc.description.notes3Dsig 2016. Pôster #56.pt_BR
dc.format.extent2p. 116-117.pt_BR
riaa.ainfo.id1060954pt_BR
riaa.ainfo.lastupdate2020-01-21 -02:00:00pt_BR
dc.contributor.institutionLUIZ BORRO, Unicamp; INACIO HENRIQUE YANO, CNPTIA; IVAN MAZONI, CNPTIA; GORAN NESHICH, CNPTIA.pt_BR
Aparece nas coleções:Resumo em anais de congresso (CNPTIA)

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