Aldehyde oxidase (AOX) is a metabolic enzyme catalyzing the oxidation of aldehyde and aza-aromatic compounds and the hydrolysis of amides, moieties frequently shared by the majority of drugs. Despite its key role in human metabolism, to date only fragmentary information about the chemical features responsible for AOX susceptibility are reported and only "very local" structure-metabolism relationships based on a small number of similar compounds have been developed. This study reports a more comprehensive coverage of the chemical space of structures with a high risk of AOX phase I metabolism in humans. More than 270 compounds were studied to identify the site of metabolism and the metabolite(s). Both electronic [supported by density functional theory (DFT) calculations] and exposure effects were considered when rationalizing the structure-metabolism relationship.aldehyde oxidase | amide hydrolysis | site of metabolism | variously decorated heterocycles | structure-metabolism relationship I n recent years, the cytochromes P450 (CYP450)-mediated metabolism has been intensively studied. As a consequence, the development of new and more efficient in silico and in vitro screening systems contributed to decrease the discontinuation rates of new drugs in clinical studies by 10% in recent years (1). In particular, several models for in silico prediction of human CYP450-mediated metabolism have been reported so far (2-4) and, more recently, for human FMO3 (5). Nevertheless, a deeper understanding of non-CYP drug enzyme metabolism is advisable to further improve screening and models efficacy (6). Among all non-CYP metabolic enzymes (7), emerging importance has been attributed to human aldehyde oxidase (hAOX), a cytosolic drugmetabolizing enzyme expressed in human liver that, similarly to CYPs, contributes to new chemical entities' oxidation, but acting in the absence of NADPH cofactor. Drugs that are substrates for AOX often exhibit high metabolic clearance, resulting in low exposure and hence in decreased drug efficacy in humans. In particular, AOX catalyzes the oxidation of a wide range of azaaromatic scaffolds at the unsubstituted carbon in ortho to the nitrogen (SI Appendix, Fig. S1 A and B), usually the most electron deficient (8). Several marketed drugs are well-known substrates of AOX (e.g., methotrexate, famciclovir, and zaleplon) (9), and several compounds have failed due to undetected AOX oxidation (e. g., BIBX1382, RO-1, FK3453, and carbazeran) (10-14). The role of AOX in drug development has become more relevant in the last few years as a result of organic synthesis strategies designed to reduce cytochromes P450-related metabolism, based on chemical modifications and decorations that have subsequently increased the drug reactivity toward AOX (11,15). In addition, AOX was recently found to be responsible for the rapid hydrolysis of an amide bond in GDC-0834 (SI Appendix, Fig. S1C), a potent inhibitor of Bruton's tyrosine kinase (16). Although the development of structure-metabolism relationships (SMRs) for hAOX ...

Gut–liver MPS offer attractive opportunities to study absorption and metabolism processes for orally administered drugs, especially prodrugs. Modelling and simulation must be included from the outset for robust study design and parameter generation.

Microphysiological systems (MPS) are complex and more physiologically realistic cellular in vitro tools that aim to provide more relevant human in vitro data for quantitative prediction of clinical pharmacokinetics while...

Aldehyde oxidase (AOX) is a molibdo-flavoenzyme that has raised great interest in recent years, since its contribution in xenobiotic metabolism has not always been identified before clinical trials, with consequent negative effects on the fate of new potential drugs. The fundamental role of AOX in metabolizing xenobiotics is also due to the attempt of medicinal chemists to stabilize candidates toward cytochrome P450 activity, which increases the risk for new compounds to be susceptible to AOX nucleophile attack. Therefore, novel strategies to predict the potential liability of new entities toward the AOX enzyme are urgently needed to increase effectiveness, reduce costs, and prioritize experimental studies. In the present work, we present the most up-to-date computational method to predict liability toward human AOX (hAOX), for applications in drug design and pharmacokinetic optimization. The method was developed using a large data set of homogeneous experimental data, which is also disclosed as Supporting Information .

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The enantiomeric forms of chiral compounds have identical physical properties but may vary greatly in their metabolism by individual enzymes. Enantioselectivity in UDP-glucuronosyl transferase (UGT) metabolism has been reported for a number of compounds and with different UGT isoforms involved. However, the impact of such individual enzyme results on overall clearance stereoselectivity is often not clear. The enantiomers of medetomidine, RO5263397, and propranolol and the epimers testosterone and epitestosterone exhibit more than 10-fold difference in glucuronidation rates by individual UGT enzymes. In this study we examined the translation of human UGT stereoselectivity to hepatic drug clearance considering the combination of multiple UGTs to overall glucuronidation, the contribution of other metabolic enzymes such as cytochromes P450, and the potential for differences in protein binding and blood/plasma partitioning. For medetomidine and RO5263397, the high individual enzyme (UGT2B10) enantioselectivity translated into ~3-to >10-fold differences in predicted human hepatic in vivo clearance. For propranolol the UGT enantioselectivity was irrelevant in the context of high cytochrome P450 (CYP) metabolism. For testosterone a complex picture emerged, due to differential epimeric selectivity of various contributing enzymes and potential for extrahepatic metabolism. Quite different patterns of CYP and UGT-mediated metabolism were observed across species, as well as differences in stereoselectivity, indicating that extrapolation from human enzyme and tissue data is essential when predicting human clearance enantioselectivity.