Mechanistic in silico modeling of bisphenols to predict estrogen and glucocorticoid disrupting potentials

Qinchang Chen, Chengzhuo Zhou, Wei Shi*, Xiaoxiang Wang, Pu Xia, Maoyong Song, Jing Liu, Hao Zhu, Xiaowei Zhang, Si Wei, Hongxia Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Endocrine disrupting chemicals (EDCs) can act as agonists, antagonists or mixed agonists/antagonists toward estrogen receptor α (ERα) and glucocorticoid receptor (GR) in a tissue- and cell-specific manner. However, the activation/inhibition mechanism by which structurally different chemicals induce various types of disruption remain ambiguous. This unrevealed theory limited the in silico modeling of EDCs and the prioritization of potential EDCs for experimental testing. As a kind of chemical widely used in manufacture, bisphenols (BPs) have attracted great attentions on their potential endocrine disrupting effects. BPs used in this study exhibited pure agonistic, pure antagonistic or mixed agonistic/antagonistic activities toward ERα and/or GR. According to the mechanistic modeling, the pure agonistic and pure antagonistic activities were attributed to a single type of protein conformation induced by BPs-ERα and/or BPs-GR interactions, whereas the mixed agonistic/antagonistic activities were attributed to multiple conformations that concomitantly exist. After interacting with BPs, the active conformation recruits coactivator to induce agonistic activity and the blocked conformation inhibits coactivator to induce antagonistic activity, whereas the concomitantly-existing multiple conformations (active, blocked and competing conformations) recruit coactivator, recruit corepressor and/or inhibit coactivator to dually induce the agonistic and antagonistic activities. Therefore, the in silico modeling in this study can not only predict ERα and GR disrupting activities but also, especially, identify the potential mechanisms. This mechanistic study breaks the current bottleneck of computational toxicology and can be widely used to prioritize potential estrogen/glucocorticoid disruptor for experimental testing in both pre-clinic and clinic studies.

Original languageEnglish
Article number138854
JournalScience of the Total Environment
Volume728
DOIs
Publication statusPublished - 1 Aug 2020

Bibliographical note

Funding Information:
This work was supported by the National Key Research and Development Program of China ( 2018YFC1801604 ), the Natural Science Foundation of China ( 21922603 , 21577058 ), the Science Fund for Excellent Young Scholars of Jiangsu Province ( BK20170077 ), and the National Water Pollution Control and Treatment Science and Technology Major Project ( 2017ZX07202-001 and 2017ZX07602-002 ).

Funding Information:
The computational calculations were performed in the High Performance Computing Center (HPCC) of Nanjing University and the National Supercomputing Center in Shenzhen. This work was supported by the National Key Research and Development Program of China (2018YFC1801604), the Natural Science Foundation of China (21922603, 21577058), the Science Fund for Excellent Young Scholars of Jiangsu Province (BK20170077), and the National Water Pollution Control and Treatment Science and Technology Major Project (2017ZX07202-001 and 2017ZX07602-002).

Publisher Copyright:
© 2020 Elsevier B.V.

Keywords

  • Accelerated molecular dynamics simulations
  • Binding free energy
  • Coregulators
  • Endocrine disruptor
  • Estrogen receptor
  • Glucocorticoid receptor

ASJC Scopus subject areas

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution

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