Network Pharmacology-Based Study on the Efficacy and Mechanism of Lonicera japonica Thunberg
Source abstract
Abstract
Network pharmacology is an emerging method for investigating the potential effects and mechanisms of natural products through system-level analyses of gene sets in herbs. Lonicera japonica Thunberg (LJ) is known to have anti-inflammatory, anti-bacterial, anti-oxidant, anti-tumor and neuroprotective effects. In the present study, network pharmacological analysis was performed to assess the potential efficacy and mechanisms of LJ. First of all, constituents of LJ were gathered from public databases: the Oriental Advanced Searching Integrated System (OASIS) database, PubChem and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Then, a network was constructed using Cytoscape3.8.2, which visualizes biomedical interactions, and a functional enrichment analysis was conducted to uncover the pathways most relevant to LJ through Enrichr based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway 2021. Further, we performed a study of the literature to determine whether the results of our study were consistent with those of previous studies. The results showed that ‘Advanced glycation end products-Receptor for advanced glycation end products (AGE-RAGE) signaling pathway in diabetic complications’ was the pathway most relevant to LJ, especially through ‘Mitogen-activated protein kinase (MAPK) signaling pathway’, ‘Phosphatidylinositol 3 kinase-Protein kinase B (PI3K-AKT) signaling pathway’ and ‘Janus kinase-Signal transducers and activators of transcription (JAK-STAT) signaling pathway’. Based on the literature study, LJ showed relevance to MAPK, PI3K-AKT and JAK-STAT and was associated with therapeutic effects on diabetes and diabetic complications. This study shows that network pharmacology can be a suitable approach for analyzing LJ and suggests the potential efficacy and mechanisms of LJ.
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Research context
OpenAlex topics: Pharmacological Effects of Natural Compounds · Computational Drug Discovery Methods · Metabolomics and Mass Spectrometry Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Convergence Korean Medical Science, College of Korean Medicine, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea
Funding
Undergraduate Research Program (URP) of the College of Korean Medicine, Kyung Hee University, Republic of Korea · Regional Innovation Strategy (RIS)
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