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Title: QSAR modeling of aromatase inhibitory activity of 1-substituted 1,2,3-triazole analogs of letrozole
Authors: Chanin Nantasenamat
Apilak Worachartcheewan
Supaluk Prachayasittikul
Chartchalerm Isarankura-Na-Ayudhya
Virapong Prachayasittikul
Mahidol University
Keywords: Chemistry;Pharmacology, Toxicology and Pharmaceutics
Issue Date: 9-Sep-2013
Citation: European Journal of Medicinal Chemistry. Vol.69, (2013), 99-114
Abstract: Aromatase is an estrogen biosynthesis enzyme belonging to the cytochrome P450 family that catalyzes the rate-limiting step of converting androgens to estrogens. As it is pertinent toward tumor cell growth promotion, aromatase is a lucrative therapeutic target for breast cancer. In the pursuit of robust aromatase inhibitors, a set of fifty-four 1-substituted mono- and bis-benzonitrile or phenyl analogs of 1,2,3-triazole letrozole were employed in quantitative structure-activity relationship (QSAR) study using multiple linear regression (MLR), artificial neural network (ANN) and support vector machine (SVM). Such QSAR models were developed using a set of descriptors providing coverage of the general characteristics of a molecule encompassing molecular size, flexibility, polarity, solubility, charge and electronic properties. Important physicochemical properties giving rise to good aromatase inhibition were obtained by means of exploring its chemical space as a function of the calculated molecular descriptors. The optimal subset of 3 descriptors (i.e. number of rings, ALogP and HOMO-LUMO) was further used for QSAR model construction. The predicted pIC50values were in strong correlation with their experimental values displaying correlation coefficient values in the range of 0.72-0.83 for the cross-validated set (QCV) while the external test set (QExt) afforded values in the range of 0.65-0.66. Insights gained from the present study are anticipated to provide pertinent information contributing to the origins of aromatase inhibitory activity and therefore aid in our on-going quest for aromatase inhibitors with robust properties. © 2013 Elsevier Masson SAS. All rights reserved.
ISSN: 17683254
Appears in Collections:Scopus 2011-2015

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