Mechanism of Rosae Rugosae Flos flavonoids in the treatment of hyperlipidemia and optimization of extraction process based on network pharmacology

Yunxiao Xia , Aijinxiu Ma , Zihan Hou , Xu Zhao

Journal of Polyphenols ›› 2024, Vol. 6 ›› Issue (2) : 65 -77.

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Journal of Polyphenols ›› 2024, Vol. 6 ›› Issue (2) :65 -77.
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Mechanism of Rosae Rugosae Flos flavonoids in the treatment of hyperlipidemia and optimization of extraction process based on network pharmacology
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Abstract

This study aims to identify a natural plant chemical with hypolipidemic effects that can be used to treat high cholesterol without adverse reactions. Through network pharmacology screening, it was found that Rosae Rugosae Flos (RF) flavonoids had potential therapeutic effects on hyperlipidemia and its mechanism of action was discussed. TCMSP and GeneCards databases were used to obtain active ingredients and disease targets. Venn diagrams were drawn to illustrate the findings. The interaction network diagram was created using Cytoscape 3.8.0 software. The PPI protein network was constructed using String. GO and KEGG enrichment analysis was performed using Metascape. The results revealed 2 active flavonoid ingredients and 60 potential targets in RF. The key targets, including CCL2, PPARG, and PPARA, were found to play a role in multiple pathways such as the AGE-RAGE signaling pathway, lipid and atherosclerosis, and cancer pathway in diabetic complications. The solvent extraction method was optimized for efficient flavonoid extraction based on network pharmacology prediction results. This was achieved through a single factor and orthogonal test, resulting in an optimum process with a reflux time of 1.5 h, a solid-liquid ratio of 1:13 g/mL, and an ethanol concentration of 50%.

Keywords

Rosae Rugosae Flos / flavonoids / extraction / process optimization / network pharmacology / hyperlipidemia

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Yunxiao Xia, Aijinxiu Ma, Zihan Hou, Xu Zhao. Mechanism of Rosae Rugosae Flos flavonoids in the treatment of hyperlipidemia and optimization of extraction process based on network pharmacology. Journal of Polyphenols, 2024, 6(2): 65-77 DOI:

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