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Structure-activity relationships (SAR) of contraceptive progestogens studied with four different methods using calculated physicochemical parameters

机译:使用计算的理化参数用四种不同方法研究避孕孕激素的构效关系(SAR)

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Structure-activity relationships (SAR) of the contraceptive progestogens for (I) oral contraceptive activity (OCA), (II) androgenic effect, and (III) binding affinity for sex hormone binding globulin (SHBG) were studied using four different methods: principal component analysis (PCA), hierarchical cluster analysis (HCA), neural networks (NN), and electronic indices method (EIM) employing descriptors calculated by the semi-empirical Austin Model 1 (AM1) method. An additional set of molecules was used to check the reliability of the results obtained for OCA by PCA. Using PCA, three different sets of descriptors were found to correlate with the three different biological activities, I-III, indicating that the interaction between the receptor and the progestogen must depend on the type of biological activity. The descriptors selected by PCA were also employed for SAR analysis of the contraceptive progestogens using two other method, HCA and NN. Both HCA and NN correctly classified high activity molecules as different from low activity ones. Thus, those descriptors selected by PCA work well in the other two methods of classification. Using the sign of ρ, a difference of electron densities of selected molecular orbitals in a specified region in a molecule, it was possible to discriminate high activity molecules from low activity molecules in the three different types of activities studied, I-III, with one exception.
机译:使用四种不同的方法研究了孕激素与(I)口服避孕活性(OCA),(II)雄激素作用和(III)对性激素结合球蛋白(SHBG)的结合亲和力之间的构效关系(SAR)。组件分析(PCA),层次聚类分析(HCA),神经网络(NN)和电子索引方法(EIM),采用通过半经验奥斯汀模型1(AM1)方法计算的描述符。使用另一组分子来检查PCA对OCA获得的结果的可靠性。使用PCA,发现三组不同的描述符与三种不同的生物活性I-III相关,这表明受体与孕激素之间的相互作用必须取决于生物活性的类型。通过PCA选择的描述语还用于HCA和NN这两种其他方法,用于避孕孕激素的SAR分析。 HCA和NN都正确地将高活性分子分类为与低活性分子不同的分子。因此,由PCA选择的那些描述符在其他两种分类方法中效果很好。利用ρ的符号(分子中特定区域内选定分子轨道的电子密度的差异),可以区分三种研究类型的I-III活性中的高活性分子与低活性分子例外。

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