Significance of Multiple Bioactivation Pathways for Meclofenamate as Revealed through Modeling and Reaction Kinetics

Abstract

Meclofenamate is a non-steroidal anti-inflammatory drug used in the treatment of mild to moderate pain yet poses a rare risk of hepatotoxicity through an unknown mechanism. NSAID bioactivation is a common molecular initiating event for hepatotoxicity. Thus, we hypothesized a similar mechanism for meclofenamate and leveraged computational and experimental approaches to identify and characterize its bioactivation. Analyses employing our XenoNet model indicated possible pathways to meclofenamate bioactivation into 19 reactive metabolites subsequently trapped into glutathione adducts. We describe the first reported bioactivation kinetics for meclofenamate and relative importance of those pathways using human liver microsomes. The findings validated only four of the many bioactivation pathways predicted by modeling. For experimental studies, dansyl glutathione was a critical trap for reactive quinone metabolites and provided a way to characterize adduct structures by mass spectrometry and quantitate yields during reactions. Of the four quinone adducts, we were able to characterize structures for three of them. Based on kinetics, the most efficient bioactivation pathway led to the monohydroxy para-quinone-imine followed by the dechloro-ortho-quinone-imine. Two very inefficient pathways led to the dihydroxy ortho-quinone and a likely multiply adducted quinone. When taken together, bioactivation pathways for meclofenamate accounted for approximately 13% of total metabolism. In sum, XenoNet facilitated prediction of reactive metabolite structures while quantitative experimental studies provided a tractable approach to validate actual bioactivation pathways for meclofenamate. Our results provide a foundation for assessing reactive metabolite load more accurately for future comparative studies with other NSAIDs and drugs in general. Significance Statement Meclofenamate bioactivation may initiate hepatotoxicity yet common risk assessment approaches are often cumbersome and inefficient and yield qualitative insights that do not scale This article has not been copyedited and formatted. The final version may differ from this version.

Novel advances in biotransformation and bioactivation research – 2020 year in review

“…It is thought that this toxicity is initiated as a result of cytochrome P450 bioactivation that forms covalent adducts to hepatic proteins and glutathione (GSH) (Galati et al, 2002). Here the investigators (Schleiff et al, 2021) used computational and experimental approaches to analyze possible key reactive metabolite formations.…”

Novel advances in biotransformation and bioactivation research—2019 year in review

“…It is thought that this toxicity is initiated as a result of cytochrome P450 bioactivation that forms covalent adducts to hepatic proteins and glutathione (GSH) (Galati et al 2002). Here the investigators (Schleiff et al 2021) used computational and experimental approaches to analyze possible key reactive metabolite formations. Through computational methods, 19 possible reactive metabolites highlighted possible reactions including metabolites resulting from monooxidation, dioxidation and/or oxidation followed by the resulting dechlorination.…”

Bioactivation of Isoxazole-Containing Bromodomain and Extra-Terminal Domain (BET) Inhibitors

“…These computational analyses are more accessible than experiments and provide an opportunity to readily explore potential relationships between molecular structure and bioactivation that lead to testable hypotheses. In practice, we couple high throughput computational studies with experimental efforts to validate predicted relationships and reveal model shortcomings for further refinement into practical tools, as shown through our work on terbinafine [16], thiazoles [17,18], and diphenylamine nonsteroidal anti-inflammatory drugs [19]. In this study, we applied our novel computational and experimental strategy to reveal the potential bioactivation liabilities of bromodomain and extra-terminal (BET) inhibitors.…”

“…Herein, we carried out a novel coupled modeling strategy to predict bioactivation pathways involving isoxazoles and validated them experimentally for selected BET inhibitors that are currently in development. The identification of possible bioactivation pathways for isoxazoles involved coupling deep neural models for quinone species formation, metabolite structures, and then biomolecule reactivity, as described previously [19]. Next, we assessed the capacity of our quinone model to identify potential electrophilic metabolites generated for isoxazole-containing molecules in the Accelrys Metabolite Database (AMD).…”

“…We carried out metabolism studies with those molecules using human liver microsomes. Reactions included dansylated glutathione to trap reactive metabolites and track adducts using the fluorescent dansyl tag [19,54,55]. A subsequent mass spectrometric (MS) characterization of the glutathione adducts provided a way to infer structures of the observed reactive metabolites.…”