QSAR modeling of nucleosides against amastigotes of Leishmania donovani using logistic regression and classification tree

dc.creatorOliveira, KMG
dc.creatorTakahata, Y
dc.date2008
dc.dateAUG
dc.date2014-11-17T23:50:49Z
dc.date2015-11-26T17:43:30Z
dc.date2014-11-17T23:50:49Z
dc.date2015-11-26T17:43:30Z
dc.date.accessioned2018-03-29T00:25:34Z
dc.date.available2018-03-29T00:25:34Z
dc.identifierQsar & Combinatorial Science. Wiley-v C H Verlag Gmbh, v. 27, n. 8, n. 1020, n. 1027, 2008.
dc.identifier1611-020X
dc.identifierWOS:000258849000007
dc.identifier10.1002/qsar.200710172
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/58513
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/58513
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/58513
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1287608
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionWe employed two classification methods; first, a logistic regression, second, classification tree, to classify nucleoside activities against Leishmania donovani using a training set of 21 compounds. The compounds are classified either active or inactive. The model was validated using a test set of 14 compounds. Two descriptors, Mor26v and Gap(HOMO, HOMO-I), were selected. The logistic regression resulted classification accuracy of 90.5% for the training set, 67% for the test set after Applicability Domain analysis was performed. The method of classification tree resulted classification accuracy of 95% for the training set, 86% for the test set. It was shown that the lowest energy conformation can be used to build a QSAR model through examination of the whole conformations that lie above the lowest energy conformation in the energy window of 13 kcal/mol. The selected descriptor Mor26v distinguishes differences in molecular chirality, while Gap(HOMO, HOMO-1) distinguishes differences in electronic structures.
dc.description27
dc.description8
dc.description1020
dc.description1027
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.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFAPESP [98/16485-1, 2007/586798]
dc.descriptionCNPq [304751/2006-5]
dc.languageen
dc.publisherWiley-v C H Verlag Gmbh
dc.publisherWeinheim
dc.publisherAlemanha
dc.relationQsar & Combinatorial Science
dc.relationQSAR Comb. Sci.
dc.rightsfechado
dc.rightshttp://olabout.wiley.com/WileyCDA/Section/id-406071.html
dc.sourceWeb of Science
dc.subjectVisceral Leishmaniasis
dc.subjectDrug Discovery
dc.subjectAntileishmanial Activity
dc.subjectTransplant Recipients
dc.subjectThymidine Kinase
dc.subjectChallenges
dc.subjectMolecules
dc.subjectDiseases
dc.subjectAnalogs
dc.subjectBinding
dc.titleQSAR modeling of nucleosides against amastigotes of Leishmania donovani using logistic regression and classification tree
dc.typeArtículos de revistas


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