Department of Biochemistry and Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States.
Department of Pathology and Immunology, Washington University, St. Louis, MO 63130, United States.
Biochem Pharmacol. 2018 Oct;156:10-21. doi: 10.1016/j.bcp.2018.07.043. Epub 2018 Aug 2.
Lamisil (terbinafine) may cause idiosyncratic liver toxicity through a proposed toxicological mechanism involving the reactive metabolite 6,6-dimethyl-2-hepten-4-ynal (TBF-A). TBF-A toxicological relevance remains unclear due to a lack of identification of pathways leading to and competing with TBF-A formation. We resolved this knowledge gap by combining computational modeling and experimental kinetics of in vitro hepatic N-dealkylation of terbinafine. A deep learning model of N-dealkylation predicted a high probability for N-demethylation to yield desmethyl-terbinafine followed by N-dealkylation to TBF-A and marginal contributions from other possible pathways. We carried out steady-state kinetic experiments with pooled human liver microsomes that relied on development of labeling methods to expand metabolite characterization. Those efforts revealed high levels of TBF-A formation and first order decay during metabolic reactions; actual TBF-A levels would then reflect the balance between those processes as well as reflect the impact of stabilizing adduction with glutathione and other biological molecules. Modeling predictions and experimental studies agreed on the significance of N-demethylation and insignificance of N-denaphthylation in terbinafine metabolism, yet differed on importance of direct TBF-A formation. Under steady-state conditions, the direct pathway was the most important source of the reactive metabolite with a V/K of 4.0 pmol/min/mg protein/µM in contrast to model predictions. Nevertheless, previous studies show that therapeutic dosing leads to accumulation of desmethyl-terbinafine in plasma, which means that likely sources for TBF-A would draw from metabolism of both the major metabolite and parent drug based on our modeling and experimental studies. Through this combination of novel modeling and experimental approaches, we are the first to identify pathways leading to generation of TBF-A for assessing its role in idiosyncratic adverse drug interactions.
兰美抒(特比萘芬)可能通过一种涉及反应性代谢物 6,6-二甲基-2-庚烯-4-炔醛(TBF-A)的毒性作用机制引起特发性肝毒性。由于缺乏导致 TBF-A 形成的途径和与 TBF-A 形成竞争的途径,TBF-A 的毒理学相关性尚不清楚。我们通过结合体外肝脱 N-烷基化特比萘芬的计算建模和实验动力学研究解决了这一知识空白。脱 N-烷基化的深度学习模型预测 N-脱甲基化生成去甲基特比萘芬,然后 N-脱烷基化生成 TBF-A 的可能性很高,而其他可能途径的贡献则微不足道。我们使用汇集的人肝微粒体进行了稳态动力学实验,该实验依赖于开发标记方法来扩展代谢产物的特征。这些努力揭示了在代谢反应过程中 TBF-A 形成和一级衰减的高水平;实际的 TBF-A 水平将反映这些过程之间的平衡,以及反映与谷胱甘肽和其他生物分子的稳定加合物的影响。模型预测和实验研究都同意 N-脱甲基化和 N-萘基化在特比萘芬代谢中的重要性,而直接 TBF-A 形成的重要性则不同。在稳态条件下,直接途径是反应性代谢物的最重要来源,其 V/K 值为 4.0 pmol/min/mg 蛋白/µM,与模型预测值形成对比。然而,先前的研究表明,治疗剂量会导致去甲基特比萘芬在血浆中积累,这意味着根据我们的建模和实验研究,TBF-A 的可能来源将来自主要代谢物和母体药物的代谢。通过这种新的建模和实验方法的结合,我们首次确定了生成 TBF-A 的途径,以评估其在特发性药物不良反应相互作用中的作用。