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Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining
Phillyrin, a well-known bisepoxylignan, has been shown to have many critical pharmacological activities. In this study, a novel strategy for the extensive acquisition and use of data was established based on UHPLC-Q-Exactive mass spectrometry to analyze and identify the in vivo metabolites of philly...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333037/ https://www.ncbi.nlm.nih.gov/pubmed/32670374 http://dx.doi.org/10.1155/2020/8274193 |
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author | Ma, Beibei Li, Jiameng Lou, Tianyu Liang, Yaoyue Wang, Chenxiao Li, Ruiji Wang, Tingting Liu, Jinhui Guo, Yudong Wang, Zhibin Wang, Jing |
author_facet | Ma, Beibei Li, Jiameng Lou, Tianyu Liang, Yaoyue Wang, Chenxiao Li, Ruiji Wang, Tingting Liu, Jinhui Guo, Yudong Wang, Zhibin Wang, Jing |
author_sort | Ma, Beibei |
collection | PubMed |
description | Phillyrin, a well-known bisepoxylignan, has been shown to have many critical pharmacological activities. In this study, a novel strategy for the extensive acquisition and use of data was established based on UHPLC-Q-Exactive mass spectrometry to analyze and identify the in vivo metabolites of phillyrin and to elucidate the in vivo metabolic pathways of phillyrin. Among them, the generation of data sets was mainly due to multichannel data mining methods, such as high extracted ion chromatogram (HEIC), diagnostic product ion (DPI), and neutral loss filtering (NLF). A total of 60 metabolites (including the prototype compound) were identified in positive and negative ion modes based on intuitive and useful data such as the standard's cleavage rule, accurate molecular mass, and chromatographic retention time. The results showed that a series of biological reactions of phillyrin in vivo mainly included methylation, hydroxylation, hydrogenation, sulfonation, glucuronidation, demethylation, and dehydrogenation and their composite reactions. In summary, this study not only comprehensively explained the in vivo metabolism of phillyrin, but also proposed an effective strategy to quickly analyze and identify the metabolites of natural pharmaceutical ingredients in nature. |
format | Online Article Text |
id | pubmed-7333037 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-73330372020-07-14 Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining Ma, Beibei Li, Jiameng Lou, Tianyu Liang, Yaoyue Wang, Chenxiao Li, Ruiji Wang, Tingting Liu, Jinhui Guo, Yudong Wang, Zhibin Wang, Jing Int J Anal Chem Research Article Phillyrin, a well-known bisepoxylignan, has been shown to have many critical pharmacological activities. In this study, a novel strategy for the extensive acquisition and use of data was established based on UHPLC-Q-Exactive mass spectrometry to analyze and identify the in vivo metabolites of phillyrin and to elucidate the in vivo metabolic pathways of phillyrin. Among them, the generation of data sets was mainly due to multichannel data mining methods, such as high extracted ion chromatogram (HEIC), diagnostic product ion (DPI), and neutral loss filtering (NLF). A total of 60 metabolites (including the prototype compound) were identified in positive and negative ion modes based on intuitive and useful data such as the standard's cleavage rule, accurate molecular mass, and chromatographic retention time. The results showed that a series of biological reactions of phillyrin in vivo mainly included methylation, hydroxylation, hydrogenation, sulfonation, glucuronidation, demethylation, and dehydrogenation and their composite reactions. In summary, this study not only comprehensively explained the in vivo metabolism of phillyrin, but also proposed an effective strategy to quickly analyze and identify the metabolites of natural pharmaceutical ingredients in nature. Hindawi 2020-06-24 /pmc/articles/PMC7333037/ /pubmed/32670374 http://dx.doi.org/10.1155/2020/8274193 Text en Copyright © 2020 Beibei Ma et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ma, Beibei Li, Jiameng Lou, Tianyu Liang, Yaoyue Wang, Chenxiao Li, Ruiji Wang, Tingting Liu, Jinhui Guo, Yudong Wang, Zhibin Wang, Jing Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining |
title | Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining |
title_full | Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining |
title_fullStr | Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining |
title_full_unstemmed | Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining |
title_short | Comprehensive Screening and Identification of Phillyrin Metabolites in Rats Based on UHPLC-Q-Exactive Mass Spectrometry Combined with Multi-Channel Data Mining |
title_sort | comprehensive screening and identification of phillyrin metabolites in rats based on uhplc-q-exactive mass spectrometry combined with multi-channel data mining |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333037/ https://www.ncbi.nlm.nih.gov/pubmed/32670374 http://dx.doi.org/10.1155/2020/8274193 |
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