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

Authors
Lee, Ji-YoonLee, Sang YoonLee, KiHoOh, Soo JinKim, Sang Kyum
Issue Date
5-3월-2015
Publisher
ELSEVIER IRELAND LTD
Keywords
Amitriptyline; CYP; UGT; Metabolic stability; Metabolite identification
Citation
CHEMICO-BIOLOGICAL INTERACTIONS, v.229, pp.109 - 118
Indexed
SCIE
SCOPUS
Journal Title
CHEMICO-BIOLOGICAL INTERACTIONS
Volume
229
Start Page
109
End Page
118
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/94146
DOI
10.1016/j.cbi.2015.01.024
ISSN
0009-2797
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. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
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