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Molecules 2012, 17(6), 7415-7439; doi:10.3390/molecules17067415
Article

Application of 4D-QSAR Studies to a Series of Raloxifene Analogs and Design of Potential Selective Estrogen Receptor Modulators

1,2,* , 1,3, 4, 2,5, 1, 2, 5, 6 and 1,*
1 Laboratory of Molecular Modeling (LabMMol), Program of Post-Graduation in Chemistry (PPGQu), Institute of Chemistry, Federal University of Rio de Janeiro (Universidade Federal do Rio de Janeiro, UFRJ), Rio de Janeiro 21949-900, RJ, Brazil 2 Laboratory of Molecular Modeling & QSAR-3D (ModMolQSAR), Faculty of Pharmacy, UFRJ, Rio de Janeiro 21941-599, RJ, Brazil 3 UFRJ, Campus UFRJ-Macaé, Macaé 27901-000, RJ, Brazil 4 Department of Chemistry, Federal University of Lavras (Universidade Federal de Lavras, UFLA), University Campus, Lavras 37200-000, MG, Brazil 5 Laboratory of Industrial Pharmaceutical Technology (LabTIF), Faculty of Pharmacy, UFRJ, Rio de Janeiro 21941-590, RJ, Brazil 6 Laboratory of Antibiotics, Biochemistry, Education and Molecular Modeling (LABiEMol), Institute of Biology (IB), Fluminense Federal University (Universidade Federal Fluminense, UFF), Campus of Valonguinho, Niterói 24210-130, RJ, Brazil
* Authors to whom correspondence should be addressed.
Received: 12 April 2012 / Revised: 4 June 2012 / Accepted: 5 June 2012 / Published: 15 June 2012
(This article belongs to the Special Issue QSAR and Its Applications)
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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.
Keywords: four dimensional quantitative structure-activity relationship (4D-QSAR); ligand based drug design (LBDD); molecular modeling; estrogen receptor alpha (ERa); estrogen receptor beta (ERb); selective estrogen receptor modulator (SERM); raloxifene; ligand binding domain (LBD) four dimensional quantitative structure-activity relationship (4D-QSAR); ligand based drug design (LBDD); molecular modeling; estrogen receptor alpha (ERa); estrogen receptor beta (ERb); selective estrogen receptor modulator (SERM); raloxifene; ligand binding domain (LBD)
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Sodero, A.C.R.; Romeiro, N.C.; da Cunha, E.F.F.; de Oliveira Magalhães, U.; de Alencastro, R.B.; Rodrigues, C.R.; Cabral, L.M.; Castro, H.C.; Albuquerque, M.G. Application of 4D-QSAR Studies to a Series of Raloxifene Analogs and Design of Potential Selective Estrogen Receptor Modulators. Molecules 2012, 17, 7415-7439.

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