Literature DB >> 24408517

Simultaneous quantification of the abundance of several cytochrome P450 and uridine 5'-diphospho-glucuronosyltransferase enzymes in human liver microsomes using multiplexed targeted proteomics.

Brahim Achour1, Matthew R Russell, Jill Barber, Amin Rostami-Hodjegan.   

Abstract

Cytochrome P450 (P450) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes mediate a major proportion of phase I and phase II metabolism of xenobiotics. In vitro-in vivo extrapolation (IVIVE) of hepatic clearance in conjunction with physiologically-based pharmacokinetics (PBPK) has become common practice in drug development. However, prediction of xenobiotic kinetics in virtual populations requires knowledge of both enzyme abundances and the extent to which these correlate. A multiplexed quantification concatemer (QconCAT) strategy was used in this study to quantify the expression of several P450 and UGT enzymes simultaneously and to establish correlations between various enzyme abundances in 24 individual liver samples (ages 27-66, 14 male). Abundances were comparable to previously reported values, including CYP2C9 (40.0 ± 26.0 pmol mg(-1)), CYP2D6 (11.9 ± 13.2 pmol mg(-1)), CYP3A4 (68.1 ± 52.3 pmol mg(-1)), UGT1A1 (33.6 ± 34.0 pmol mg(-1)), and UGT2B7 (82.9 ± 36.1 pmol mg(-1)), expressed as mean ± S.D. Previous reports of correlations in expression of various P450 (CYP3A4/CYP3A5*1/*3, CYP2C8/CYP2C9, and CYP3A4/CYP2B6) were confirmed. New correlations were demonstrated between UGTs [including UGT1A6/UGT1A9 (r(s) = 0.82, P < 0.0001) and UGT2B4/UGT2B15 (r(s) = 0.71, P < 0.0001)]. Expression of some P450 and UGT enzymes were shown to be correlated [including CYP1A2/UGT2B4 (r(s) = 0.67, P = 0.0002)]. The expression of CYP3A5 in individuals with *1/*3 genotype (n = 11) was higher than those with *3/*3 genotype (n = 10) (P < 0.0001). No significant effect of gender or history of smoking or alcohol use on enzyme expression was observed; however, expression of several enzymes declined with age. The correlation matrix produced for the first time by this study can be used to generate more realistic virtual populations with respect to abundance of various enzymes.

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Year:  2014        PMID: 24408517     DOI: 10.1124/dmd.113.055632

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  40 in total

1.  Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper.

Authors:  Bhagwat Prasad; Brahim Achour; Per Artursson; Cornelis E C A Hop; Yurong Lai; Philip C Smith; Jill Barber; Jacek R Wisniewski; Daniel Spellman; Yasuo Uchida; Michael A Zientek; Jashvant D Unadkat; Amin Rostami-Hodjegan
Journal:  Clin Pharmacol Ther       Date:  2019-07-26       Impact factor: 6.875

2.  Multiplexed Targeted Quantitative Proteomics Predicts Hepatic Glucuronidation Potential.

Authors:  Guillaume Margaillan; Michèle Rouleau; Kathrin Klein; John K Fallon; Patrick Caron; Lyne Villeneuve; Philip C Smith; Ulrich M Zanger; Chantal Guillemette
Journal:  Drug Metab Dispos       Date:  2015-06-15       Impact factor: 3.922

3.  Choice of LC-MS methods for the absolute quantification of drug-metabolizing enzymes and transporters in human tissue: a comparative cost analysis.

Authors:  Hajar Al Feteisi; Brahim Achour; Jill Barber; Amin Rostami-Hodjegan
Journal:  AAPS J       Date:  2015-02-06       Impact factor: 4.009

4.  Accounting for inter-correlation between enzyme abundance: a simulation study to assess implications on global sensitivity analysis within physiologically-based pharmacokinetics.

Authors:  Nicola Melillo; Adam S Darwich; Paolo Magni; Amin Rostami-Hodjegan
Journal:  J Pharmacokinet Pharmacodyn       Date:  2019-03-23       Impact factor: 2.745

5.  Repository Describing an Aging Population to Inform Physiologically Based Pharmacokinetic Models Considering Anatomical, Physiological, and Biological Age-Dependent Changes.

Authors:  Felix Stader; Marco Siccardi; Manuel Battegay; Hannah Kinvig; Melissa A Penny; Catia Marzolini
Journal:  Clin Pharmacokinet       Date:  2019-04       Impact factor: 6.447

Review 6.  Quantitative targeted proteomics for membrane transporter proteins: method and application.

Authors:  Xi Qiu; Hui Zhang; Yurong Lai
Journal:  AAPS J       Date:  2014-05-15       Impact factor: 4.009

7.  A Comprehensive Whole-Body Physiologically Based Pharmacokinetic Model of Dabigatran Etexilate, Dabigatran and Dabigatran Glucuronide in Healthy Adults and Renally Impaired Patients.

Authors:  Daniel Moj; Hugo Maas; André Schaeftlein; Nina Hanke; José David Gómez-Mantilla; Thorsten Lehr
Journal:  Clin Pharmacokinet       Date:  2019-12       Impact factor: 6.447

8.  Comparative Proteomics Analysis of Human Liver Microsomes and S9 Fractions.

Authors:  Xinwen Wang; Bing He; Jian Shi; Qian Li; Hao-Jie Zhu
Journal:  Drug Metab Dispos       Date:  2019-11-07       Impact factor: 3.922

9.  Enzyme Kinetics of Uridine Diphosphate Glucuronosyltransferases (UGTs).

Authors:  Jin Zhou; Upendra A Argikar; John O Miners
Journal:  Methods Mol Biol       Date:  2021

10.  Determining Allele-Specific Protein Expression (ASPE) Using a Novel Quantitative Concatamer Based Proteomics Method.

Authors:  Jian Shi; Xinwen Wang; Huaijun Zhu; Hui Jiang; Danxin Wang; Alexey Nesvizhskii; Hao-Jie Zhu
Journal:  J Proteome Res       Date:  2018-09-04       Impact factor: 4.466

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