Quantitative structure-activity relationship of compounds binding to estrogen receptor β based on heuristic method

Abstract

Estrogen compounds may pose a serious threat to the health of humans and wildlife. The estrogen receptor (ER) exists as two subtypes, ER and ER. Compounds might have different relative affinities and binding modes for ER and ER. In this study, the heuristic method was performed on 31 compounds binding to ER to select 5 variances most related to the activity (LogRBA) from 1524 variances, which were then employed to develop the best model with the significant correlation and the best predictive power (r 2 = 0.829, q 2 LOO = 0.742, r 2 pred = 0.772, q 2 ext = 0.724, RMSEE = 0.395) using multiple linear regression (MLR). The model derived identified critical structural features related to the activity of binding to ER. The applicability domain (AD) of the model was assessed by Williams plot. estrogen receptor  (ER), quantitative structure-activity relationship (QSAR), heuristic method, applicability domain

Prediction of the heat capacity for compounds based on the conjugate gradient and support vector machine methods

“…The larger the absolute value of the correlation coefficient is, the greater the correlation degree is. In Table I, it shows that the correlation coefficients are all less than 0.7 and according to the literature [35], the selected molecular descriptors are suitable as input parameters of the model.…”

“…In this study, the applicability domain (AD) of models was defined by the leverage value. The analysis was made in the Williams plot whose plot is of standardized residuals versus the leverage values.…”

3D-QSAR and pharmacophore model study on aryl diphenolic azoles as estrogen receptor-β ligands

“…In the past several years, the medicinal chemistry modeling studies of ERb ligands have been performed by different authors, including docking and quantitative structure-activity relationship (QSAR) techniques (Barrett et al, 2008;Wolohan and Reichert, 2007;Beeley and Sage, 2003;Norman et al, 2006;Henke et al, 2002;Taha et al, 2010;Asikainen et al, 2006;Li et al, 2006;Zhang et al, 2011;Waller, 2004;Xiao et al, 2008). Although X-ray crystal structures of ERb are available, docking approaches are not accurate to predict binding affinities of ERb ligands because of some serious problems (Barrett et al, 2008;Wolohan and Reichert, 2007;Beeley and Sage, 2003; Luan et al (2008) reported that accurate prediction of binding affinities of aryl diphenolic azoles remains difficult and the classification of binding affinities of diverse compounds to some extent may be feasible.…”

Quantitative Structure Activity Relationship of New 7-Oxycoumarin Derivatives as Potent and Selective Monoamine Oxidase a Inhibitors

“…Instead of arduous, expensive laboratory work and the great number of animal tests, the biological activity was predicted solely on the basis of the molecular structure of the compound by quantitative structure-activity relationship (QSAR) techniques, which can also identify the structural features related to the activity, thus having increasingly more applications in the drug design [13][14][15][16][17]. The current QSAR model is associated with the following information: (1) a defined endpoint, (2) an unambiguous algorithm, (3) a defined domain of applicability, (4) appropriate measures of goodness-of-fit, robustness and predictivity, and (5) a mechanistic interpretation [18]. In this article, using the heuristic method, we set up a linear model to describe the relationship between the molecular structures and the selectivity toward MAO-A isoenzyme.…”