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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Nonequivalent Effects of Diverse LogP Algorithms in Three QSAR Studies

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Autor(es):
de Melo, Eduardo Borges [1, 2] ; Castro Ferreira, Marcia Miguel [1]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] Univ Estadual Campinas, Inst Chem, Theoret & Appl Chemometr Lab, BR-13083970 Campinas, SP - Brazil
[2] Univ Estadual Oeste Parana, Ctr Ciencias Med & Farmaceut, Curso Farm, BR-85819110 Cascavel, Parana - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: QSAR & COMBINATORIAL SCIENCE; v. 28, n. 10, p. 1156-1165, OCT 2009.
Citações Web of Science: 6
Resumo

Despite of the availability and facility of accessing several algorithms for calculation of LogP in QSA(P)R studies, articles typically do not describe the selection procedure for the method used. Therefore, three studies to verify the influence of different LogP algorithms on building QSAR models were performed. Two QSAR data sets from the literature (forty-two tricyclic phtalimide inhibitors of HIV-integrase and fourty-six TIBO derivatives inhibitors of HIV-reverse transcriptase) were used together with LogP calculated by thirteen algorithms, and several regression models were constructed and compared. A new QSAR study for 4,5-dihydroxvpyrimidine carboxamides inhibitors of HIV-1 integrase was also performed. The explained and predicted variance, results from external validation, leave-N-out cross-validation and y-randomization test were analyzed for all models from the three data sets. Despite the same physicochemical meaning, LogP's calculated by distinct methods may show different levels of contribution to the model. This observation comes out from the comparison of validated models. These results indicate that the arbitrary choice of one specific algorithm for LogP calculation, as is usual in QSA(P)R studies, does not necessarily lead to the highest quality model for the analyzed data set. (AU)

Processo FAPESP: 04/04686-5 - Abordagens quimiométricas clássicas e novas em estudos teóricos de substâncias bioativas
Beneficiário:Marcia Miguel Castro Ferreira
Modalidade de apoio: Auxílio à Pesquisa - Temático