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Título: | Application of 4D-QSAR studies to a series of raloxifene analogs and design of potential selective estrogen receptor modulators |
Palavras-chave: | Molecular modeling Estrogen receptor Raloxifene Genetic algorithms Modelagem molecular Receptor de estrogênio Raloxifeno Algorítmos genéticos |
Data do documento: | 2012 |
Editor: | MDPI |
Citação: | SODERO, A. C. R. et al. Application of 4D-QSAR studies to a series of raloxifene analogs and design of potential selective estrogen receptor modulators. Molecules, [S. l.], v. 17, p. 7415-7439, 2012. |
Resumo: | Four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis was applied on a series of 54 2-arylbenzothiophene derivatives, synthesized by Grese and coworkers, based on raloxifene (an estrogen receptor-alpha antagonist), and evaluated as ERa ligands and as inhibitors of estrogen-stimulated proliferation of MCF-7 breast cancer cells. The conformations of each analogue, sampled from a molecular dynamics simulation, were placed in a grid cell lattice according to three trial alignments, considering two grid cell sizes (1.0 and 2.0 Å). The QSAR equations, generated by a combined scheme of genetic algorithms (GA) and partial least squares (PLS) regression, were evaluated by “leave-one-out” cross-validation, using a training set of 41 compounds. External validation was performed using a test set of 13 compounds. The obtained 4D-QSAR models are in agreement with the proposed mechanism of action for raloxifene. This study allowed a quantitative prediction of compounds’ potency and supported the design of new raloxifene analogs. |
URI: | http://www.mdpi.com/1420-3049/17/6/7415 http://repositorio.ufla.br/jspui/handle/1/28483 |
Aparece nas coleções: | DQI - Artigos publicados em periódicos |
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