Computational study of estrogen receptor-alpha antagonist with three-dimensional quantitative structure-activity relationship, support vector regression, and linear regression methods.

International Journal of Medicinal Chemistry Pub Date : 2013-01-01 Epub Date: 2013-05-14 DOI:10.1155/2013/743139
Ying-Hsin Chang, Jun-Yan Chen, Chiou-Yi Hor, Yu-Chung Chuang, Chang-Biau Yang, Chia-Ning Yang
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引用次数: 8

Abstract

Human estrogen receptor (ER) isoforms, ERα and ERβ, have long been an important focus in the field of biology. To better understand the structural features associated with the binding of ERα ligands to ERα and modulate their function, several QSAR models, including CoMFA, CoMSIA, SVR, and LR methods, have been employed to predict the inhibitory activity of 68 raloxifene derivatives. In the SVR and LR modeling, 11 descriptors were selected through feature ranking and sequential feature addition/deletion to generate equations to predict the inhibitory activity toward ERα. Among four descriptors that constantly appear in various generated equations, two agree with CoMFA and CoMSIA steric fields and another two can be correlated to a calculated electrostatic potential of ERα.

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雌激素受体- α拮抗剂三维定量构效关系、支持向量回归和线性回归方法的计算研究。
人雌激素受体(ER)的同种异构体ERα和ERβ一直是生物学领域的一个重要研究热点。为了更好地了解ERα配体与ERα结合的结构特征并调节其功能,采用CoMFA、CoMSIA、SVR和LR等QSAR模型预测了68种雷洛昔芬衍生物的抑制活性。在SVR和LR建模中,通过特征排序和顺序添加/删除特征,选择11个描述符,生成方程来预测对ERα的抑制活性。在各种生成的方程中不断出现的四个描述符中,有两个与CoMFA和CoMSIA空间场一致,另外两个可以与计算出的ERα静电势相关。
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期刊介绍: International Journal of Medicinal Chemistry is a peer-reviewed, Open Access journal that publishes original research articles as well as review articles in all areas of chemistry associated with drug discovery, design, and synthesis. International Journal of Medicinal Chemistry is a peer-reviewed, Open Access journal that publishes original research articles as well as review articles in all areas of chemistry associated with drug discovery, design, and synthesis.
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