Exploring the potential mechanisms of Ferulic Acid for treating COVID-19 based on Network Pharmacology and Molecular Docking as well as experimental verification
2023
Shengchao Zhao | Yuanhui Wang | Ziyi Shen | Guanzhen Wang | Xiaomeng Hu | Wei Liu | Yi Cai | Tingdong Yan | Chunpeng (Craig) Wan
Using network pharmacology, we aimed to examine the underlying mechanisms of FA in treating COVID-19. GeneCards and OMIM were queried for information on FA treatment and COVID-19 targets. The PPI network was obtained using the software Cytoscape. GO and KEGG enrichment analyses were used to identify biological pathways associated with the target proteins. Using AutoDock Tools, simulate molecular docking and predict the extent of FA binding to key targets. In <i>in vitro</i> cell experiments, A549 served as the object, various concentrations of FA were used to prepare the cell model, and qRT-PCR was used to detect the expression of TLR4, ACE, and EGFR genes. Network pharmacology screened 18 FA and COVID-19 intersection targets, enriched 1594 GO entries, and targeted the regulation of the inflammatory response. 29 KEGG pathways involving COVID-19, NF-B, and Toll-like receptor signalling were significantly enriched. Cell experiments confirm that FA can effectively inhibit the expression of TLR4, ACE, and EGFR. This study aims to shed new light on the search for potential COVID-19 treatments.
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