Software‐aided cytochrome P450 reaction phenotyping and kinetic analysis in early drug discovery. (14th December 2015)

• Record Type: Journal Article
• Authors: Cece‐Esencan, Esra Nurten; Fontaine, Fabien; Plasencia, Guillem; Teppner, Marieke; Brink, Andreas; Pähler, Axel; Zamora, Ismael
• Is Part Of: Rapid communications in mass spectrometry. Volume 30:Number 2(2016)
• Page Start: 301
• Page End: 310
• Publication Date: 2015-12-14
• Subjects: Mass spectrometry -- Periodicals; 543.65
• DOI: 10.1002/rcm.7429
• Languages: English
• ISSNs: 0951-4198

Abstract

Abstract : Rationale: Cytochrome P450 (CYP450) reaction phenotyping (CRP) and kinetic studies are essential in early drug discovery to determine which metabolic enzymes react with new drug entities. A new semi‐automated computer‐assisted workflow for CRP is introduced in this work. This workflow provides not only information regarding parent disappearance, but also metabolite identification and relative metabolite formation rates for kinetic analysis. Methods: Time‐course experiments based on incubating six probe substrates (dextromethorphan, imipramine, buspirone, midazolam, ethoxyresorufin and diclofenac) with recombinant human enzymes (CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) and human liver microsomes (HLM) were performed. Liquid chromatography/high‐resolution mass spectrometry (LC/HRMS) analysis was conducted with an internal standard to obtain high‐resolution full‐scan and MS/MS data. Data were analyzed using Mass‐MetaSite software. A server application (WebMetabase) was used for data visualization and review. Results: CRP experiments were performed, and the data were analyzed using a software‐aided approach. This automated‐evaluation approach led to (1) the detection of the CYP450 enzymes responsible for both substrate depletion and metabolite formation, (2) the identification of specific biotransformations, (3) the elucidation of metabolite structures based on MS/MS fragment analysis, and (4) the determination of the initial relative formation rates of major metabolites by CYP450 enzymes. Conclusions: This largely automated workflow enabled the efficient analysis of HRMS data, allowing rapid evaluation of the involvement of the main CYP450 enzymes in the metabolism of new molecules during drug discovery. Copyright © 2015 John Wiley & Sons, Ltd.