MIA-QSPR and effect of variable selection on the modeling of kinetic parameters related to activities of modified peptides against dengue type 2

dc.creatorSilla, JM
dc.creatorNunes, CA
dc.creatorCormanich, RA
dc.creatorGuerreiro, MC
dc.creatorRamalho, TC
dc.creatorFreitas, MP
dc.date2011
dc.dateOCT 15
dc.date2014-07-30T14:01:38Z
dc.date2015-11-26T16:07:55Z
dc.date2014-07-30T14:01:38Z
dc.date2015-11-26T16:07:55Z
dc.date.accessioned2018-03-28T22:56:34Z
dc.date.available2018-03-28T22:56:34Z
dc.identifierChemometrics And Intelligent Laboratory Systems. Elsevier Science Bv, v. 108, n. 2, n. 146, n. 149, 2011.
dc.identifier0169-7439
dc.identifierWOS:000295310000008
dc.identifier10.1016/j.chemolab.2011.06.009
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/56665
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/56665
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1266253
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionMultivariate image analysis applied to quantitative structure-property relationship (MIA-QSPR) has shown to be a useful tool to model the biochemical properties of a series of drug-like compounds. However, drawing and alignment of two-dimensional structures (the images) are usually performed manually, resulting in a few imperfections. Selection of descriptors, which are in fact pixels of images, can minimize such effects; also, it enables selection of those variables which indeed explains the variance in the activities block. Therefore, in order to obtain more parsimonious, predictive models, interval PLS (iPLS), genetic algorithm (GA), and ordered predictors selection (OPS) were applied to select appropriate MIA descriptors to model kinetic constants, namely substrate cleavage rate (k(cat)) and Michaelis (K(m)) constants, which correlate to the bioactivities of peptides against Dengue type 2 (DEN-2). The models built were used to predict k(cat) and K(m) of new proposed peptides, which are miscellany of substructures of the most promising peptides experimentally tested elsewhere. (C) 2011 Elsevier B.V. All rights reserved.
dc.description108
dc.description2
dc.description146
dc.description149
dc.descriptionFundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionPETROBRAS
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.languageen
dc.publisherElsevier Science Bv
dc.publisherAmsterdam
dc.publisherHolanda
dc.relationChemometrics And Intelligent Laboratory Systems
dc.relationChemometrics Intell. Lab. Syst.
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectMIA-QSPR
dc.subjectDengue type 2
dc.subjectPeptides
dc.subjectGenetic algorithm
dc.subjectInterval PLS
dc.subjectOrdered predictor selection
dc.subjectMolecular-biology
dc.subjectQsar
dc.subjectSpectroscopy
dc.subjectRegression
dc.titleMIA-QSPR and effect of variable selection on the modeling of kinetic parameters related to activities of modified peptides against dengue type 2
dc.typeArtículos de revistas


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