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

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	Mechanistic in silico modeling of bisphenols to predict estrogen and glucocorticoid disrupting potentials
	Chen, Qinchang; Zhou, Chengzhuo; Shi, Wei; Wang, Xiaoxiang; Xia, Pu; Song, Maoyong; Liu, Jing; Zhu, Hao; Zhang, Xiaowei; Wei, Si
刊名	SCIENCE OF THE TOTAL ENVIRONMENT
	2020-08-01
卷号	728 页码:1-11
关键词	Endocrine disruptor Estrogen receptor Glucocorticoid receptor Coregulators Accelerated molecular dynamics simulations Binding free energy
ISSN号	0048-9697
英文摘要	Endocrine disrupting chemicals (EDCs) can act as agonists, antagonists or mixed agonists/antagonists toward estrogen receptor alpha (ER alpha) 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 ER alpha 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-ER alpha 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 ERa 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. (C) 2020 Elsevier B.V. All rights reserved.
内容类型	期刊论文
源URL	[http://ir.rcees.ac.cn/handle/311016/44877]
专题	生态环境研究中心_环境纳米材料实验室
推荐引用方式 GB/T 7714	Chen, Qinchang,Zhou, Chengzhuo,Shi, Wei,et al. Mechanistic in silico modeling of bisphenols to predict estrogen and glucocorticoid disrupting potentials[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2020,728:1-11.
APA	Chen, Qinchang.,Zhou, Chengzhuo.,Shi, Wei.,Wang, Xiaoxiang.,Xia, Pu.,...&Yu, Hongxia.(2020).Mechanistic in silico modeling of bisphenols to predict estrogen and glucocorticoid disrupting potentials.SCIENCE OF THE TOTAL ENVIRONMENT,728,1-11.
MLA	Chen, Qinchang,et al."Mechanistic in silico modeling of bisphenols to predict estrogen and glucocorticoid disrupting potentials".SCIENCE OF THE TOTAL ENVIRONMENT 728(2020):1-11.