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Molecules. 2012 Jun 15;17(6):7415-39. doi: 10.3390/molecules17067415.

Application of 4D-QSAR studies to a series of raloxifene analogs and design of potential selective estrogen receptor modulators.

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  • 1Laboratory of Molecular Modeling-LabMMol, Program of Post-Graduation in Chemistry-PPGQu, Institute of Chemistry, Federal University of Rio de Janeiro-UFRJ, Rio de Janeiro 21949-900, RJ, Brazil. acrsodero@gmail.com

Abstract

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.

PMID:
22706372
[PubMed - indexed for MEDLINE]
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