Identification of androgen receptor antagonists: In vitro investigation and classification methodology for flavonoid. (September 2016)

• Record Type: Journal Article
• Authors: Wu, Yang; Doering, Jon A.; Ma, Zhiyuan; Tang, Song; Liu, Hongling; Zhang, Xiaowei; Wang, Xiaoxiang; Yu, Hongxia
• Is Part Of: Chemosphere. Volume 158(2016)
• Page Start: 72
• Page End: 79
• Publication Date: 2016-09
• Subjects: Methodology -- Androgen -- Flavonoids -- MD simulations -- QSAR -- CoMSIA; Pollution -- Periodicals; Pollution -- Physiological effect -- Periodicals; Environmental sciences -- Periodicals; Atmospheric chemistry -- Periodicals; 551.511
• DOI: 10.1016/j.chemosphere.2016.05.059
• Languages: English
• ISSNs: 0045-6535

Abstract

Abstract: A tremendous gap exists between the number of potential endocrine disrupting chemicals (EDCs) possibly in the environment and the limitation of traditional regulatory testing. In this study, the anti-androgenic potencies of 21 flavonoids were analyzed in vitro, and another 32 flavonoids from the literature were selected as additional chemicals. Molecular dynamic simulations were employed to obtain four different separation approaches based on the different behaviors of ligands and receptors during the process of interaction. Specifically, ligand-receptor complex which highlighted the discriminating features of ligand escape or retention via "mousetrap" mechanism, hydrogen bonds formed during simulation times, ligand stability and the stability of the helix-12 of the receptor were investigated. Together, a methodology was generated that 87.5% of flavonoids could be discriminated as active versus inactive antagonists, and over 90% inactive antagonists could be filtered out before QSAR study. This methodology could be used as a "proof of concept" to identify inactive anti-androgenic flavonoids, as well could be beneficial for rapid risk assessment and regulation of multiple new chemicals for androgenicity. Graphical abstract: Highlights: AR-antagonist of different flavonoids were analyzed in vitro and in silico . A methodology based on four approaches that saves labor-intense assays was generated. The methodology could filter out over 90% inactive AR-antagonists.