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Combining docking and comparative molecular similarity indices analysis (COMSIA) to predict estrogen activity and probe molecular mechanisms of estrogen activity for estrogen compounds
作者姓名:YANG XuShu  ;WANG XiaoDong  ;JI Li  ;LI Rong  ;SUN Cheng  ;WANG LianSheng
作者单位:[1]State Key Laboratory of Pollution Control and Resources Reuse, School of Environment, Nanjing University, Nanjing 210093, China; [2]School of Pharmacy, Nanjing Medical University, Nanjing 210029, China
基金项目:Supported by National Natural Science Foundation of China (Grant No. 20507008), National Natural Science Foundation Key Project of China (Grant No. 20737001) and National Basic Research Program of China (973 Program) (Grant No. 2003CB415002)
摘    要:Estrogen compounds are suspected of disrupting endocrine functions by mimicking natural hormones, and such compounds may pose a serious threat to the health of humans and wildlife. Close attention has been paid to the prediction and molecular mechanisms of estrogen activity for estrogen com- pounds. In this article, estrogen receptor a subtype (ERa) -based comparative molecular similarity indices analysis (COMSIA) was performed on 44 estrogen compounds with structural diversity to find out the structural relationship with the activity and to predict the activity. The model with the significant correlation and the best predictive power (R^2= 0.965, Q^2 LOO: 0.599, R^2 pred : 0.825) was achieved. The COMSIA and docking results revealed the structural features for estrogen activity and key amino acid residues in binding pocket, and provided an insight into the interaction between the ligands and these amino acid residues.

关 键 词:雌性激素  混合物  受感器  分子组成
收稿时间:2008-04-12
修稿时间:2008-09-15

Combining docking and comparative molecular similarity indices analysis (COMSIA) to predict estrogen activity and probe molecular mechanisms of estrogen activity for estrogen compounds
YANG XuShu,;WANG XiaoDong,;JI Li,;LI Rong,;SUN Cheng,;WANG LianSheng.Combining docking and comparative molecular similarity indices analysis (COMSIA) to predict estrogen activity and probe molecular mechanisms of estrogen activity for estrogen compounds[J].Chinese Science Bulletin,2008,53(23):3626-3633.
Authors:XuShu Yang  XiaoDong Wang  Li Ji  Rong Li  Cheng Sun  LianSheng Wang
Institution:(1) State Key Laboratory of Pollution Control and Resources Reuse, School of Environment, Nanjing University, Nanjing, 210093, China;(2) School of Pharmacy, Nanjing Medical University, Nanjing, 210029, China
Abstract:Estrogen compounds are suspected of disrupting endocrine functions by mimicking natural hormones, and such compounds may pose a serious threat to the health of humans and wildlife. Close attention has been paid to the prediction and molecular mechanisms of estrogen activity for estrogen compounds. In this article, estrogen receptor α subtype (ERα) -based comparative molecular similarity indices analysis (COMSIA) was performed on 44 estrogen compounds with structural diversity to find out the structural relationship with the activity and to predict the activity. The model with the significant correlation and the best predictive power (R 2 = 0.965, Q 2 LOO = 0.599, R 2 pred = 0.825) was achieved. The COMSIA and docking results revealed the structural features for estrogen activity and key amino acid residues in binding pocket, and provided an insight into the interaction between the ligands and these amino acid residues. Supported by National Natural Science Foundation of China (Grant No. 20507008), National Natural Science Foundation Key Project of China (Grant No. 20737001) and National Basic Research Program of China (973 Program) (Grant No. 2003CB415002)
Keywords:estrogen compounds  receptor-based  docking  comparative molecular similarity indices analysis (COMSIA)  quantitative structure-activity relationship (QSAR)
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