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Title 

Determination of species-difference in microsomal metabolism of amitriptyline using a predictive MRM-IDA-EPI method

Authors 

J Y LeeS Y LeeK LeeSoo Jin OhS K Kim

Publisher 

Elsevier

Issue Date 

2015

Citation 

Chemico-Biological Interactions, vol. 229, no. 0, pp. 109-118

Keywords 

AmitriptylineCYPMetabolic stabilityMetabolite identificationUGT

Abstract 

We investigated to compare species differences in amitriptyline (AMI) metabolism among mouse, rat, dog, and human liver microsomes. We developed a method for simultaneous determination of metabolic stability and metabolite profiling using predictive multiple reaction monitoring information-dependent acquisition-enhanced product ion (MRM-IDA-EPI) scanning. In the cofactor-dependent microsomal metabolism study, AMI was metabolized more rapidly in rat and human liver microsomes incubated with NADPH than UDPGA. AMI incubated with NADPH + UDPGA in rat, dog, or mouse liver microsomes disappeared rapidly with a half-life of 3.5, 8.4, or 9.2 min, respectively, but slowly in human liver microsomes with a half-life of 96 min. In total, 9, 10, 11, and 6 putative metabolites of AMI were detected in mouse, rat, dog, and human liver microsomes, respectively, based on mass spectrometric analyses. Kinetic analysis of metabolites in liver microsomes from each species over 120 min showed common metabolic routes of AMI, such as N-demethylation, hydroxylation, and glucuronidation, and subtle interspecies differences in AMI metabolism. The main metabolic routes in mouse, rat, dog, and human liver microsomes were hydroxylation followed by glucuronide conjugation, methyl hydroxylation, and N-demethylation, respectively. The MRM-IDA-EPI method can provide quantitative and qualitative information about metabolic stability and metabolite profiling simultaneously. Moreover, time course analysis of metabolites can not only eliminate false identification of metabolites, but also provide a rationale for proposed metabolic pathways. The MRM-IDA-EPI method combined with time course analysis of metabolites is useful for investigating drug metabolism at the early drug discovery stage.

ISSN 

0009-2797

Link 

http://dx.doi.org/10.1016/j.cbi.2015.01.024

Appears in Collections

1. Journal Articles > Journal Articles

Registered Date

2019-05-02


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