Zhang Miao-Qing, Zhang Jing-Pu, Hu Chang-Qin
Key Laboratory of Biotechnology of Antibiotics, The National Health Commission (NHC), Beijing Key Laboratory of Antimicrobial Agents, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
National Institutes for Food and Drug Control, Beijing, China.
Front Pharmacol. 2022 Apr 4;13:860702. doi: 10.3389/fphar.2022.860702. eCollection 2022.
Impurities in pharmaceuticals of potentially hazardous materials may cause drug safety problems. Macrolide antibiotic preparations include active pharmaceutical ingredients (APIs) and different types of impurities with similar structures, and the amount of these impurities is usually very low and difficult to be separated for toxicity evaluation. Our previous study indicated that hepatotoxicity induced by macrolides was correlated with c-fos overexpression. Here, we report an assessment of macrolide-related liver toxicity by ADMET prediction, molecular docking, structure-toxicity relationship, and experimental verification detection of the gene expression in liver cells. The results showed that a rapid assessment model for the prediction of hepatotoxicity of macrolide antibiotics could be established by calculation of the -CDOCKER interaction energy score with the FosB/JunD bZIP domain and then confirmed by the detection of the gene expression in L02 cells. Telithromycin, a positive compound of liver toxicity, was used to verify the correctness of the model through comparative analysis of liver toxicity in zebrafish and cytotoxicity in L02 cells exposed to telithromycin and azithromycin. The prediction interval (48.1∼53.1) for quantitative hepatotoxicity in the model was calculated from the docking scores of seven macrolide antibiotics commonly used in clinics. We performed the prediction interval to virtual screening of azithromycin impurities with high hepatotoxicity and then experimentally confirmed by liver toxicity in zebrafish and gene expression. Simultaneously, we found the hepatotoxicity of azithromycin impurities may be related to the charge of nitrogen (N) atoms on the side chain group at the C5 position structure-toxicity relationship of azithromycin impurities with different structures. This study provides a theoretical basis for improvement of the quality of macrolide antibiotics.
药品中潜在有害物质的杂质可能会引发药物安全问题。大环内酯类抗生素制剂包含活性药物成分(API)以及不同类型结构相似的杂质,且这些杂质的含量通常极低,难以分离用于毒性评估。我们之前的研究表明,大环内酯类药物诱导的肝毒性与c-fos过表达相关。在此,我们通过ADMET预测、分子对接、结构-毒性关系以及肝细胞基因表达的实验验证来报告对大环内酯类相关肝毒性的评估。结果显示,通过计算与FosB/JunD bZIP结构域的-CDOCKER相互作用能得分,随后通过检测L02细胞中的基因表达进行确认,可建立一种预测大环内酯类抗生素肝毒性的快速评估模型。肝毒性阳性化合物泰利霉素通过对斑马鱼肝毒性以及暴露于泰利霉素和阿奇霉素的L02细胞毒性的比较分析,用于验证该模型的正确性。该模型中定量肝毒性的预测区间(48.1∼53.1)是根据七种临床常用大环内酯类抗生素的对接得分计算得出的。我们利用该预测区间对具有高肝毒性的阿奇霉素杂质进行虚拟筛选,然后通过斑马鱼肝毒性和基因表达进行实验确认。同时,我们发现阿奇霉素杂质的肝毒性可能与C5位侧链基团上氮(N)原子的电荷有关——不同结构的阿奇霉素杂质的结构-毒性关系。本研究为提高大环内酯类抗生素的质量提供了理论依据。