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Updated: Jun 12, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Computational studies of interactions between endocrine disrupting chemicals and androgen receptor of different
Bing Wu1, Timothy Ford, Ji-Dong Gu
1Nanjing University, China.
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.
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