Cargando…
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...
Autores principales: | , , , , , , , , |
---|---|
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 |
_version_ | 1784634112958529536 |
---|---|
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. |
format | Online Article Text |
id | pubmed-8764198 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT gulifei chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity AT xiexueqing chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity AT wangbing chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity AT jinyibao chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity AT wanglijun chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity AT yinguo chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity AT wangjue chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity AT bikaishun chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity AT wangtiejie chemicalpatternrecognitionforqualityanalysisofloniceraejaponicaeflosandloniceraeflosbasedonultrahighperformanceliquidchromatographyandantisarscov2mainproteaseactivity |