MIA-QSAR, PC-Ranking and least-squares support-vector machines in the accurate prediction of the activities of Phosphodiesterase Type 5 (PDE-5) inhibitors

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorGoodarzi, Mohammad-
Autor(es): dc.creatorFreitas, Matheus P.-
Data de aceite: dc.date.accessioned2026-02-09T11:26:10Z-
Data de disponibilização: dc.date.available2026-02-09T11:26:10Z-
Data de envio: dc.date.issued2020-07-12-
Data de envio: dc.date.issued2020-07-12-
Data de envio: dc.date.issued2010-10-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/41807-
Fonte completa do material: dc.identifierhttps://www.tandfonline.com/doi/full/10.1080/08927022.2010.490261-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1140752-
Descrição: dc.descriptionPhosphodiesterase type-5 (PDE-5) is a key enzyme involved in the erection process. PDE-5 inhibitors, such as Sildenafil (ViagraTM), Vardenafil (LevitraTM) and Tadalafil (CialisTM), are used for the treatment of erectile dysfunction. Computer-assisted modelling of biological activities of PDE-5 inhibitors may make quantitative structure–activity relationship (QSAR) models useful for the development of safer (low side effects) and more potent drugs. The multivariate image analysis applied to QSAR (MIA-QSAR) method, coupled to partial least-squares (PLS) regression, has provided highly predictive QSAR models. Nevertheless, regression methods which take into account nonlinearity, such as least-squares support-vector machines (LS-SVMs), are supposed to predict biological activities more accurately than the usual linear methods. Thus, together with prior variable selection using principal component analysis ranking, MIA-QSAR and LS-SVM regression were applied to model the bioactivities of a series of cyclic guanine derivatives (PDE-5 inhibitors), and the results were compared with those based on linear methodologies. MIA-QSAR/LS-SVM was found to improve greatly the prediction performance when compared with MIA-QSAR/PLS, MIA-QSAR/N-PLS, CoMFA/PLS and CoMSIA/PLS models.-
Idioma: dc.languageen-
Publicador: dc.publisherTaylor & Francis-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceMolecular Simulation-
Palavras-chave: dc.subjectMIA-QSAR-
Palavras-chave: dc.subjectPCA ranking-
Palavras-chave: dc.subjectLS-SVM-
Palavras-chave: dc.subjectPDE-5-
Palavras-chave: dc.subjectMultivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR)-
Palavras-chave: dc.subjectPrincipal component analysis (PCA)-
Palavras-chave: dc.subjectLeast squares support vector machine (LS-SVM)-
Título: dc.titleMIA-QSAR, PC-Ranking and least-squares support-vector machines in the accurate prediction of the activities of Phosphodiesterase Type 5 (PDE-5) inhibitors-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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