Literature DB >> 20546840

Computational studies of interactions between endocrine disrupting chemicals and androgen receptor of different vertebrate species.

Bing Wu1, Timothy Ford, Ji-Dong Gu, Xu-Xiang Zhang, Ai-Min Li, Shu-Pei Cheng.   

Abstract

Homology modeling and molecular docking were used to in silico analyze the interactions between six endocrine disrupting chemicals (EDCs) and 11 androgen receptors (ARs) of different vertebrate species. The MODELLER 9V7 program was employed to construct the homology models of AR ligand binding domains (LBDs) from birds, amphibians, bony fishes and cartilaginous fishes. The Surflex-Dock program was applied to calculate and analyze the binding affinities between the six EDCs and AR LBDs. The docking experiment showed that AR LBDs had high affinities with nonyl phenol (NP) and butyl benzyl phthalate (BBP), but low affinities with the 2,2',4,4',5,5'-hexabromodiphenyl ether (BDE153). The results of cluster analysis suggested that predicted binding affinities were species-specific, which was consistent with the phylogenetic analysis of AR LBDs. The difference of binding affinities could be mainly due to the different hydrogen bonds and the orientation of ligands in the binding pockets. Our results suggest that integrated methods of phylogenetic analysis, homology modeling and molecular docking might be a potential tool to predict the different interactions between contaminants and associated receptors in different trophic levels. 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20546840     DOI: 10.1016/j.chemosphere.2010.04.043

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  3 in total

1.  Designing Endocrine Disruption Out of the Next Generation of Chemicals.

Authors:  T T Schug; R Abagyan; B Blumberg; T J Collins; D Crews; P L DeFur; S M Dickerson; T M Edwards; A C Gore; L J Guillette; T Hayes; J J Heindel; A Moores; H B Patisaul; T L Tal; K A Thayer; L N Vandenberg; J Warner; C S Watson; F S Vom Saal; R T Zoeller; K P O'Brien; J P Myers
Journal:  Green Chem       Date:  2013-01       Impact factor: 10.182

2.  Understanding lignin-degrading reactions of ligninolytic enzymes: binding affinity and interactional profile.

Authors:  Ming Chen; Guangming Zeng; Zhongyang Tan; Min Jiang; Hui Li; Lifeng Liu; Yi Zhu; Zhen Yu; Zhen Wei; Yuanyuan Liu; Gengxin Xie
Journal:  PLoS One       Date:  2011-09-29       Impact factor: 3.240

3.  A computational approach to evaluate the androgenic affinity of iprodione, procymidone, vinclozolin and their metabolites.

Authors:  Corrado Lodovico Galli; Cristina Sensi; Amos Fumagalli; Chiara Parravicini; Marina Marinovich; Ivano Eberini
Journal:  PLoS One       Date:  2014-08-11       Impact factor: 3.240

  3 in total

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