Innovations in Food and Chemical Safety Programme and Bioinformatics Institute, Agency for Science, Technology, and Research, Singapore, Singapore.
Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore, Singapore, Singapore.
Arch Toxicol. 2021 Sep;95(9):3031-3048. doi: 10.1007/s00204-021-03111-2. Epub 2021 Jun 28.
Cytochrome P450 1A1 (CYP1A1) metabolizes estrogens, melatonin, and other key endogenous signaling molecules critical for embryonic/fetal development. The enzyme has increasing expression during pregnancy, and its inhibition or knockout increases embryonic/fetal lethality and/or developmental problems. Here, we present a virtual screening model for CYP1A1 inhibitors based on the orthosteric and predicted allosteric sites of the enzyme. Using 1001 reference compounds with CYP1A1 activity data, we optimized the decision thresholds of our model and classified the training compounds with 68.3% balanced accuracy (91.0% sensitivity and 45.7% specificity). We applied our final model to 11 known CYP1A1 orthosteric binders and related compounds, and found that our ranking of the known orthosteric binders generally agrees with the relative activity of CYP1A1 in metabolizing these compounds. We also applied the model to 22 new test compounds with unknown/unclear CYP1A1 inhibitory activity, and predicted 16 of them are CYP1A1 inhibitors. The CYP1A1 potency and modes of inhibition of these 22 compounds were experimentally determined. We confirmed that most predicted inhibitors, including drugs contraindicated during pregnancy (amiodarone, bicalutamide, cyproterone acetate, ketoconazole, and tamoxifen) and environmental agents suspected to be endocrine disruptors (bisphenol A, diethyl and dibutyl phthalates, and zearalenone), are indeed potent inhibitors of CYP1A1. Our results suggest that virtual screening may be used as a rapid tier-one method to screen for potential CYP1A1 inhibitors, and flag them out for further experimental evaluations.
细胞色素 P450 1A1（CYP1A1）代谢雌激素、褪黑素和其他对胚胎/胎儿发育至关重要的关键内源性信号分子。该酶在怀孕期间表达增加，其抑制或敲除会增加胚胎/胎儿致死率和/或发育问题。在这里，我们基于该酶的正构和预测变构位点，提出了一种 CYP1A1 抑制剂的虚拟筛选模型。使用具有 CYP1A1 活性数据的 1001 种参考化合物，我们优化了模型的决策阈值，并以 68.3%的平衡准确率（91.0%的灵敏度和 45.7%的特异性）对训练化合物进行分类。我们将最终模型应用于 11 种已知的 CYP1A1 正构结合物和相关化合物，发现我们对已知正构结合物的排序通常与 CYP1A1 代谢这些化合物的相对活性一致。我们还将模型应用于 22 种具有未知/不清楚 CYP1A1 抑制活性的新测试化合物，并预测其中 16 种为 CYP1A1 抑制剂。这些 22 种化合物的 CYP1A1 效力和抑制模式通过实验确定。我们证实，大多数预测抑制剂，包括在怀孕期间禁忌的药物（胺碘酮、比卡鲁胺、醋酸环丙孕酮、酮康唑和他莫昔芬）和疑似内分泌干扰物的环境剂（双酚 A、邻苯二甲酸二乙酯和邻苯二甲酸二丁酯、玉米赤霉烯酮），确实是 CYP1A1 的强效抑制剂。我们的结果表明，虚拟筛选可以用作快速筛选潜在 CYP1A1 抑制剂的一级方法，并将其标记出来以供进一步的实验评估。
