Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/41801
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dc.creatorGoodarzi, Mohammad-
dc.creatorFreitas, Matheus Puggina de-
dc.date.accessioned2020-07-12T20:48:53Z-
dc.date.available2020-07-12T20:48:53Z-
dc.date.issued2010-
dc.identifier.citationGOODARZI, M.; FREITAS, M. P. MIA-QSAR modeling of activities of a series of AZT analogues: bi- and multilinear PLS regression. Molecular Simulation, [S.l.], v. 36, n. 4, p. 267-272, 2010. DOI: 10.1080/08927020903278001.pt_BR
dc.identifier.urihttps://www.tandfonline.com/doi/abs/10.1080/08927020903278001pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/41801-
dc.description.abstractThe activities of a series of azidothymidine derivatives, compounds with anti-HIV potency, were computationally modelled using multivariate image analysis applied to quantitative structure–activity relationships (MIA-QSAR). Two regression methods were tested in order to find the best correlation between actual and predicted activities: bilinear (traditional) partial least squares (PLS), applied to the unfolded dataset, and multilinear PLS (N-PLS), applied to the three-way array. The predictive abilities of the PLS- and N-PLS-based models were found to be nearly equivalent, and both the methods derived QSAR models that are statistically superior to conventional QSAR, in which physicochemical descriptors and multiple linear regression were applied.pt_BR
dc.languageen_USpt_BR
dc.publisherTaylor & Francispt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceMolecular Simulationpt_BR
dc.subjectMIA-QSARpt_BR
dc.subjectAZT analoguespt_BR
dc.subjectHIVpt_BR
dc.subjectPLSpt_BR
dc.subjectN-PLSpt_BR
dc.subjectMultivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR)pt_BR
dc.subjectAzidothymidine (AZT)pt_BR
dc.subjectPartial least squares (PLS)pt_BR
dc.subjectMultiway partial least squares (N-PLS)pt_BR
dc.titleMIA-QSAR modeling of activities of a series of AZT analogues: bi- and multilinear PLS regressionpt_BR
dc.typeArtigopt_BR
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