Literature DB >> 32888045

Systematic comparison of metabolic differences of Uncaria rhynchophylla in rat, mouse, dog, pig, monkey and human liver microsomes.

Hao-Jv Li1,2, Wen-Long Wei1, Zhen-Wei Li1,2, Chang-Liang Yao1, Meng-Yuan Wang1,2, Jian-Qing Zhang1, Jia-Yuan Li1, De-An Guo3,4.   

Abstract

Metabolites have a close relationship with the efficacy and safety of herbal medicines. However, ubiquitous matrix interferences, complex co-elution, and minor or trace amounts in plasma restrict the comprehensive identification of metabolites. In this study, an efficient strategy comprising a mass defect filter and time-staggered targeted ion lists was established to characterize the metabolites of alkaloids of Uncaria rhynchophylla (UR) for the systematic comparison of metabolic differences in rat, mouse, dog, pig, monkey and human liver microsomes. The mass defect filter model effectively decreased interfering ions by 63-68%, and time-staggered precursor ion lists significantly increased the number of triggered MS/MS fragmentation by 65-120% in liver microsomes of six species. Ultimately, a total of 165 metabolites in the liver microsomes of six species were tentatively characterized, and the main metabolic pathways were demethylation, isomerization, hydrolysis, oxygenation and dehydrogenation. The results showed that the mouse liver microsomes exhibited metabolic behavior most similar to human metabolism of UR alkaloids. We hope that these results provide basic data for further investigation of UR metabolism in different species, and that the strategy can provide a reference for metabolite characterization of herbal medicines in complex biological matrix. Graphical abstract.

Entities:  

Keywords:  Indole alkaloids; Liver microsomes; Mass defect filter; Metabolite identification; Time-staggered targeted ion lists; Uncaria rhynchophylla

Mesh:

Year:  2020        PMID: 32888045     DOI: 10.1007/s00216-020-02922-z

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  1 in total

1.  Exploration of Q-Marker of Rhubarb Based on Intelligent Data Processing Techniques and the AUC Pooled Method.

Authors:  Jiayun Chen; Xiaojuan Jiang; Chunyan Zhu; Lu Yang; Minting Liu; Mingshe Zhu; Caisheng Wu
Journal:  Front Pharmacol       Date:  2022-03-21       Impact factor: 5.810

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.