Elucidating the aryl hydrocarbon receptor antagonism from a chemical-structural perspective

The aryl hydrocarbon receptor (AhR) plays an important role in several biological processes such as reproduction, immunity and homoeostasis. However, little is known on the chemical-structural and physicochemical features that influence the activity of AhR antagonistic modulators. In the present report, in vitro AhR antagonistic activity evaluations, based on a chemical-activated luciferase gene expression (AhR-CALUX) bioassay, and an extensive literature review were performed with the aim of constructing a structurally diverse database of contaminants and potentially toxic chemicals. Subsequently, QSAR models based on Linear Discriminant Analysis and Logistic Regression, as well as two toxicophoric hypotheses were proposed to model the AhR antagonistic activity of the built dataset. The QSAR models were rigorously validated yielding satisfactory performance for all classification parameters. Likewise, the toxicophoric hypotheses were validated using a diverse set of 350 decoys, demonstrating adequate robustness and predictive power. Chemical interpretations of both the QSAR and toxicophoric models suggested that hydrophobic constraints, the presence of aromatic rings and electron-acceptor moieties are critical for the AhR antagonism. Therefore, it is hoped that the deductions obtained in the present study will contribute to elucidate further on the structural and physicochemical factors influencing the AhR antagonistic activity of chemical compounds.

芳香烃受体（aryl hydrocarbon receptor, AhR）在生殖、免疫及稳态等多种生物学过程中发挥重要作用。然而，目前学界对影响AhR拮抗调节剂活性的化学结构与理化特征仍知之甚少。本研究基于化学激活荧光素酶基因表达（AhR-CALUX）生物分析法开展体外AhR拮抗活性评价，并结合全面的文献调研，旨在构建一个结构多样的污染物与潜在有毒化学品数据库。后续，本研究基于线性判别分析与逻辑回归构建定量结构-活性关系（Quantitative Structure-Activity Relationship, QSAR）模型，同时提出两类毒性药效团假说，以对所构建数据集的AhR拮抗活性进行建模。经严格验证，所有分类参数均取得了令人满意的分类性能。此外，本研究使用包含350个诱饵分子的多样化数据集对上述毒性药效团假说进行验证，结果证实其具备良好的稳健性与预测能力。对QSAR模型与药效团模型的化学解析表明，疏水约束、芳香环的存在以及电子受体基团是影响AhR拮抗活性的关键因素。综上，本研究所得结论有望为进一步阐明调控化合物AhR拮抗活性的结构与理化因素提供重要参考。