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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.

ABSTRACT: 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.

SUBMITTER: Gu L

PROVIDER: S-EPMC8764198 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundRespiratory Syncytial Virus (RSV) stands out as a primary contributor to lower respiratory tract infections and hospitalizations, particularly in infants. Lonicerae japonicae flos (LJF), a traditional Chinese medicine renowned for its efficacy against various viral infections, including RSV, has been widely employed. Despite its common use, the precise therapeutic mechanism of LJF against RSV remains elusive. This study aimed to investigate the underlying mechanism of LJF against RSV through network pharmacology and metabolomics.MethodsIn this study, based on network pharmacology, potential targets related to LJF and RSV were obtained from PubChem and Swiss Target Prediction. The core targets and pathways were established and verified by enrichment analysis and molecular docking. The anti-RSV efficacy of LJF was determined by in vitro experiments. Additionally, metabolomics analysis was integrated, allowing for the identification of differential metabolites and their correlation with targets following LJF treatment in the context of RSV infection.ResultsA total of 23 active ingredients and 780 targets were obtained, of which 102 targets were associated with LJF anti-RSV. The construction of the corresponding Protein-Protein Interaction (PPI) network unveiled potential core targets, including STAT3, TNF, and AKT1. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that LJF's anti-RSV effects primarily involve key pathways such as the PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, and FoxO signaling pathway. Molecular docking showed that ZINC03978781, 4,5'-Retro-.beta.,.beta.-Carotene -3,3'-dione, 4',5'-didehydro and 7-epi-Vogeloside had better binding ability. The cellular assay showed that the therapeutic index of LJF against RSV was 4.79. Furthermore, 18 metabolites were screened as potential biomarkers of LJF against RSV, and these metabolites were mainly involved in the pathways of purine metabolism, linoleic acid metabolism, alpha-linolenic acid metabolism, and other related pathways.ConclusionsThe intergration of network pharmacology and metabolomics can clarify the active targets and related pathways of LJF against RSV, which could provide a valuable reference for further research and clinical application of LJF.

Dataset Information

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.

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