As lead optimization efforts have successfully reduced metabolic liabilities due to cytochrome P450 (CYP)-mediated metabolism, there has been an increase in the frequency of involvement of non-CYP enzymes in the metabolism of investigational compounds. Although there have been numerous notable advancements in the characterization of non-CYP enzymes with respect to their localization, reaction mechanisms, species differences and identification of typical substrates, accurate prediction of non-CYP-mediated clearance, with a particular emphasis with the difficulties in accounting for any extrahepatic contributions, remains a challenge. The current manuscript comprehensively summarizes the recent advancements in the prediction of drug metabolism and the to extrapolation of clearance for substrates of non-CYP drug metabolizing enzymes.
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http://dx.doi.org/10.1080/03602532.2021.1923728 | DOI Listing |
Drug Metab Dispos
November 2024
Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands (L.M.J., C.H., D.-J.B., M.H., N.J.P, M.L.M); Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands (J.J.S); Centre for Human Drug Research, Leiden, Netherlands (R.R.); Division of Biotherapeutics, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands (R.R.); Department of Dermatology, Leiden University Medical Center, Leiden, The Netherlands (R.R.)
Compromised hepatic drug metabolism in response to proinflammatory cytokine release is primarily attributed to downregulation of cytochrome P450 (CYP) enzymes. However, whether inflammation also affects other phase I and phase II drug metabolizing enzymes (DMEs), such as the flavin monooxygenases (FMOs), carboxylesterases (CESs), and UDP glucuronosyltransferases (UGTs), remains unclear. This study aimed to decipher the impact of physiologically relevant concentrations of proinflammatory cytokines on expression and activity of phase I and phase II enzymes, to establish a hierarchy of their sensitivity as compared with the CYPs.
View Article and Find Full Text PDFCurr Res Toxicol
July 2024
Comparative Perinatal Development, Department of Veterinary Sciences, University of Antwerp, Wilrijk, Belgium.
Hepatology
July 2024
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research (NCTR), U.S. Food and Drug Administration, Jefferson, Arkansas, USA.
Background And Aims: DILI frequently contributes to the attrition of new drug candidates and is a common cause for the withdrawal of approved drugs from the market. Although some noncytochrome P450 (non-CYP) metabolism enzymes have been implicated in DILI development, their association with DILI outcomes has not been systematically evaluated.
Approach And Results: In this study, we analyzed a large data set comprising 317 drugs and their interactions in vitro with 42 non-CYP enzymes as substrates, inducers, and/or inhibitors retrieved from historical regulatory documents using multivariate logistic regression.
Clin Pharmacokinet
June 2024
Drug Clinical Trial Center, Peking University Third Hospital, Beijing, 100191, China.
Introduction: The activity changes of cytochrome P450 (CYP450) enzymes, along with the complicated medication scenarios in diabetes mellitus (DM) patients, result in the unanticipated pharmacokinetics (PK), pharmacodynamics (PD), and drug-drug interactions (DDIs). Physiologically based pharmacokinetic (PBPK) modeling has been a useful tool for assessing the influence of disease status on CYP enzymes and the resulting DDIs. This work aims to develop a novel diabetic PBPK population model to facilitate the prediction of PK and DDI in DM patients.
View Article and Find Full Text PDFbioRxiv
May 2024
Department of Pharmaceutical Sciences, Washington State University, Spokane, WA, 99202.
We examined the effect of alcohol consumption and smoking on the abundance of drug-metabolizing enzymes and transporters (DMET) in human liver microsomes (HLM) isolated from liver tissues of 94 donors. Global proteomics analysis was performed and DMET protein levels were analyzed in relation to alcohol consumption levels, smoking history, and sex using non-parametric tests (p-value ≤ 0.05; cutoff of 1.
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