Literature DB >> 17349808

Structural and chemical basis for enhanced affinity and potency for a large series of estrogen receptor ligands: 2D and 3D QSAR studies.

Lívia de B Salum1, Igor Polikarpov, Adriano D Andricopulo.   

Abstract

The estrogen receptor (ER) is an important drug target for the development of novel therapeutic agents for the treatment of breast cancer. Progress towards the design of more potent and selective ER modulators requires the optimization of multiple ligand-receptor interactions. Comparative molecular field analyses (CoMFA) and hologram quantitative structure-activity relationships (HQSAR) were conducted on a large set of ERalpha modulators. Two training sets containing either 127 or 69 compounds were used to generate QSAR models for in vitro binding affinity and potency, respectively. Significant correlation coefficients (affinity models, CoMFA, r(2)=0.93 and q(2)=0.79; HQSAR, r(2)=0.92 and q(2)=0.71; potency models, CoMFA, r(2)=0.94 and q(2)=0.72; HQSAR, r(2)=0.92 and q(2)=0.74) were obtained, indicating the potential of the models for untested compounds. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. The final QSAR models as well as the information gathered from 3D contour maps should be useful for the design of novel ERalpha modulators having improved affinity and potency.

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Year:  2007        PMID: 17349808     DOI: 10.1016/j.jmgm.2007.02.001

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  9 in total

Review 1.  Fragment-based QSAR: perspectives in drug design.

Authors:  Lívia B Salum; Adriano D Andricopulo
Journal:  Mol Divers       Date:  2009-01-31       Impact factor: 2.943

2.  Receptor based 3D-QSAR to identify putative binders of Mycobacterium tuberculosis Enoyl acyl carrier protein reductase.

Authors:  Ashutosh Kumar; Mohammad Imran Siddiqi
Journal:  J Mol Model       Date:  2009-09-25       Impact factor: 1.810

3.  Prediction of binding affinity for estrogen receptor alpha modulators using statistical learning approaches.

Authors:  Yonghua Wang; Yan Li; Jun Ding; Yuan Wang; Yaqing Chang
Journal:  Mol Divers       Date:  2008-07-26       Impact factor: 2.943

Review 4.  Recent advances in fragment-based QSAR and multi-dimensional QSAR methods.

Authors:  Kyaw Zeyar Myint; Xiang-Qun Xie
Journal:  Int J Mol Sci       Date:  2010-10-08       Impact factor: 5.923

5.  Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches.

Authors:  Liying Zhang; Alexander Sedykh; Ashutosh Tripathi; Hao Zhu; Antreas Afantitis; Varnavas D Mouchlis; Georgia Melagraki; Ivan Rusyn; Alexander Tropsha
Journal:  Toxicol Appl Pharmacol       Date:  2013-05-23       Impact factor: 4.219

6.  Fragment-based and classical quantitative structure-activity relationships for a series of hydrazides as antituberculosis agents.

Authors:  Carolina H Andrade; Livia de B Salum; Marcelo S Castilho; Kerly F M Pasqualoto; Elizabeth I Ferreira; Adriano D Andricopulo
Journal:  Mol Divers       Date:  2008-03-29       Impact factor: 2.943

7.  Metal-free O-H/C-H difunctionalization of phenols by o-hydroxyarylsulfonium salts in water.

Authors:  Dengfeng Chen; Qingyuan Feng; Yunqin Yang; Xu-Min Cai; Fei Wang; Shenlin Huang
Journal:  Chem Sci       Date:  2016-11-04       Impact factor: 9.825

8.  Comparative QSAR analysis of cyclo-oxygenase2 inhibiting drugs.

Authors:  Arumugam Mohanapriya; Dayalan Achuthan
Journal:  Bioinformation       Date:  2012-04-30

9.  Two- and three-dimensional quantitative structure-activity relationships studies on a series of liver x receptor ligands.

Authors:  Káthia M Honório; Lívia B Salum; Richard C Garratt; Igor Polikarpov; Adriano D Andricopulo
Journal:  Open Med Chem J       Date:  2008-10-07
  9 in total

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