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Study on the Effect of Three CYP2C9 Variants on Drug–Drug Interaction Related to Six Drugs In Vitro by LC–MS/MS Method

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Abstract

The influence of genetic polymorphism of metabolic enzymes on drug–drug interactions (DDI) should be thoroughly investigated owing to its remarkable effect on therapeutic treatments that are futile. Here, different from earlier articles focused on various CYP subfamilies and their isoforms, the effect of genetic polymorphs of a particular isoform, CYP2C9, was comprehensively studied. Using diclofenac as probe substrate, the influence of three CYP2C9 variants (CYP2C9*1, *2 and *3) on DDI was conducted from the measurement of inhibitory ability of six drugs towards three variants. A modified LC–MS/MS method according to former report was constructed for the determination of 4ʹ-hydroxydiclofenac in CYP2C9 enzyme incubation system and validated for accuracy, precision, linearity range within the acceptance criteria for regulatory guidelines. After selecting appropriate incubation time and enzyme concentration, the kinetic parameters of three CYP2C9 variants towards diclofenac were examined and half inhibitory concentrations (IC50) of six drugs towards three CYP2C9 variants were determined. IC50 of paroxetine and losartan towards CYP2C9*2 were almost threefold higher and 2.5-fold lower than that towards CYP2C9*1, respectively. IC50 of glibenclamide towards CYP2C9*3 was twofold more than that towards CYP2C9*1. Our results could offer effective guidelines for co-administration of these six drugs with various CYP2C9 substrates in individuals carrying variant CYP2C9 alleles, also broaden the application area of LC–MS/MS.

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Abbreviations

ADME:

Absorption, distribution, metabolism and excretion

DDI:

Drug–drug interaction

CYP450:

Cytochromes P450

IC50 :

Half inhibitory concentrations

PBS:

Phosphate buffer solution

IS:

Internal standard

QC:

Quality control

MRM:

Multiple reaction monitoring

K m :

Michaelis–Menten constant

V max :

Maximum velocity

Clint :

Intrinsic clearance

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Acknowledgements

The present research was financially supported by National Science and Technology Major Project of China (No. 2016YFC0904903), Major Project of Science and Technology of Tianjin (No. 16ZXXYSY00020), Science and Technology Department of Hubei Province (No. 2020CFB237), the Department of Education of Hubei province (No. D20201604) and Key Laboratory of Deep Proceeding of Major Gain and Oil (Wuhan Polytechnic University), Ministry of Education (No. 2020JYBQGDKFB08).

Funding

This article was funded by National Major Science and Technology Projects of China (Grant no. 2016YFC0904903), Major Project of Science and Technology of Tianjin (Grant no. 16ZXXYSY00020), Hubei Technological Innovation Special Fund (Grant no. 2020CFB237), Hubei Provincial Department of Education (Grant no. D20201604), Key Laboratory of Deep Proceeding of Major Gain and Oil (Wuhan Polytechnic University) and Ministry of Education (Grant no. 2020JYBQGDKFB08).

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Author notes

  1. Zhiping Sun and Lingli He contributed equally to this work.

Authors and Affiliations

  1. College of Food Science and Engineering, Wuhan Polytechnic University, Wuhan, 430023, China

    Zhiping Sun, Haizhi Zhang, Xinguang Qin, Gang Liu & Zhongze Hu

  2. Tianjin Key Laboratory of Molecular Design and Drug Discovery, Tianjin Institute of Pharmaceutical Research, Tianjin, 300193, China

    Lingli He, Weiren Xu & Changxiao Liu

  3. Department of Industrial Pharmacy, China Pharmaceutical University, Nanjing, 210009, China

    Lingli He, Weiren Xu & Luyong Zhang

  4. Department of Pharmacognosy, Tianjin Key Laboratory for Biomarkers of Occupational and Environmental Hazard, Logistics University of Chinese People’s Armed Police Forces, Tianjin, 300309, China

    Qingqing Yang

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  1. Zhiping Sun
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Sun, Z., He, L., Yang, Q. et al. Study on the Effect of Three CYP2C9 Variants on Drug–Drug Interaction Related to Six Drugs In Vitro by LC–MS/MS Method. Chromatographia 85, 221–231 (2022). https://doi.org/10.1007/s10337-021-04126-8

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