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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Mechanistic in silico modeling of bisphenols to predict estrogen and glucocorticoid disrupting potentials
Qinchang Chen1, Chengzhuo Zhou1, Wei Shi1
1State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, Jiangsu 210023, People's Republic of China; Jiangsu Environmental Monitoring Center, Nanjing University, Nanjing, Jiangsu 210023, People's Republic of China; Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, Nanjing University, Nanjing, Jiangsu 210023, People's Republic of China.
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.
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