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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) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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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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