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Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity

Lonicerae japonicae flos (L. japonicae flos, Lonicera japonica Thunb.) is one of the most commonly prescribed botanical drugs in the treatment or prevention of corona virus disease 2019. However, L. japonicae flos is often confused or adulterated with Lonicerae flos (L. flos, Lonicera macrantha (D.D...

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Autores principales: Gu, Lifei, Xie, Xueqing, Wang, Bing, Jin, Yibao, Wang, Lijun, Yin, Guo, Wang, Jue, Bi, Kaishun, Wang, Tiejie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764198/
https://www.ncbi.nlm.nih.gov/pubmed/35058788
http://dx.doi.org/10.3389/fphar.2021.810748
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author Gu, Lifei
Xie, Xueqing
Wang, Bing
Jin, Yibao
Wang, Lijun
Yin, Guo
Wang, Jue
Bi, Kaishun
Wang, Tiejie
author_facet Gu, Lifei
Xie, Xueqing
Wang, Bing
Jin, Yibao
Wang, Lijun
Yin, Guo
Wang, Jue
Bi, Kaishun
Wang, Tiejie
author_sort Gu, Lifei
collection PubMed
description Lonicerae japonicae flos (L. japonicae flos, Lonicera japonica Thunb.) is one of the most commonly prescribed botanical drugs in the treatment or prevention of corona virus disease 2019. However, L. japonicae flos is often confused or adulterated with Lonicerae flos (L. flos, Lonicera macrantha (D.Don) Spreng., Shanyinhua in Chinese). The anti-SARS-CoV2 activity and related differentiation method of L. japonicae flos and L. flos have not been documented. In this study, we established a chemical pattern recognition model for quality analysis of L. japonicae flos and L. flos based on ultra-high performance liquid chromatography (UHPLC) and anti-SARS-CoV2 activity. Firstly, chemical data of 59 batches of L. japonicae flos and L. flos were obtained by UHPLC, and partial least squares-discriminant analysis was applied to extract the components that lead to classification. Next, anti-SARS-CoV2 activity was measured and bioactive components were acquired by spectrum-effect relationship analysis. Finally, characteristic components were explored by overlapping feature extracted components and bioactive components. Accordingly, eleven characteristic components were successfully selected, identified, quantified and could be recommended as quality control marker. In addition, chemical pattern recognition model based on these eleven components was established to effectively discriminate L. japonicae flos and L. flos. In sum, the demonstrated strategy provided effective and highly feasible tool for quality assessment of natural products, and offer reference for the quality standard setting.
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spelling pubmed-87641982022-01-19 Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity Gu, Lifei Xie, Xueqing Wang, Bing Jin, Yibao Wang, Lijun Yin, Guo Wang, Jue Bi, Kaishun Wang, Tiejie Front Pharmacol Pharmacology Lonicerae japonicae flos (L. japonicae flos, Lonicera japonica Thunb.) is one of the most commonly prescribed botanical drugs in the treatment or prevention of corona virus disease 2019. However, L. japonicae flos is often confused or adulterated with Lonicerae flos (L. flos, Lonicera macrantha (D.Don) Spreng., Shanyinhua in Chinese). The anti-SARS-CoV2 activity and related differentiation method of L. japonicae flos and L. flos have not been documented. In this study, we established a chemical pattern recognition model for quality analysis of L. japonicae flos and L. flos based on ultra-high performance liquid chromatography (UHPLC) and anti-SARS-CoV2 activity. Firstly, chemical data of 59 batches of L. japonicae flos and L. flos were obtained by UHPLC, and partial least squares-discriminant analysis was applied to extract the components that lead to classification. Next, anti-SARS-CoV2 activity was measured and bioactive components were acquired by spectrum-effect relationship analysis. Finally, characteristic components were explored by overlapping feature extracted components and bioactive components. Accordingly, eleven characteristic components were successfully selected, identified, quantified and could be recommended as quality control marker. In addition, chemical pattern recognition model based on these eleven components was established to effectively discriminate L. japonicae flos and L. flos. In sum, the demonstrated strategy provided effective and highly feasible tool for quality assessment of natural products, and offer reference for the quality standard setting. Frontiers Media S.A. 2022-01-04 /pmc/articles/PMC8764198/ /pubmed/35058788 http://dx.doi.org/10.3389/fphar.2021.810748 Text en Copyright © 2022 Gu, Xie, Wang, Jin, Wang, Yin, Wang, Bi and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Gu, Lifei
Xie, Xueqing
Wang, Bing
Jin, Yibao
Wang, Lijun
Yin, Guo
Wang, Jue
Bi, Kaishun
Wang, Tiejie
Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity
title Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity
title_full Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity
title_fullStr Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity
title_full_unstemmed Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity
title_short Chemical Pattern Recognition for Quality Analysis of Lonicerae Japonicae Flos and Lonicerae Flos Based on Ultra-High Performance Liquid Chromatography and Anti-SARS-CoV2 Main Protease Activity
title_sort chemical pattern recognition for quality analysis of lonicerae japonicae flos and lonicerae flos based on ultra-high performance liquid chromatography and anti-sars-cov2 main protease activity
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764198/
https://www.ncbi.nlm.nih.gov/pubmed/35058788
http://dx.doi.org/10.3389/fphar.2021.810748
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