Abstract
Asthma is a chronic inflammatory disease of the airways that seriously endangers human health. Belamcanda chinensis (BC), a traditional Chinese medicine, has been used to counteract asthma as it has been shown to possess anti-inflammatory and regulatory immunity properties. The study aimed to investigate the mechanisms of action of BC in the treatment of asthma; a "dose-effect weighted coefficient" network pharmacology method was established to predict potential active compounds. Information on the components and content of BC was obtained by UPLC-QEOrbitrap- MS spectrometry. Based on BC content, oral bioavailability, and molecular docking binding energy, dose-effect weighting coefficients were constructed. With the degree greater than average as the index, a protein-protein interaction (PPI) database was used to obtain the core key targets for asthma under dose-effect weighting. GO function and KEGG pathway analyses of the core targets were performed using DAVID software. Finally, MTT and ELISA assays were used to assess the effects of active components on 16HBE cell proliferation. The experimental results using the 16HBE model demonstrated BC to have a potential protective effect on asthma. Network pharmacology showed SYK, AKT1, and ALOX5 to be the main key targets, and Fc epsilon RI as the promising signaling pathway. Eight components, such as tectoridin, mangiferin, luteolin, and isovitexin were the main active compounds, Finally, we analyzed the LPS-induced 16HBE proliferation of each active ingredient. Based on the activity verification study, all five predicted components promoted the proliferation of 16HBE cells. These five compounds can be used as potential quality markers for asthma. This study provides a virtual and practical method for the simple and rapid screening of active ingredients in natural products.
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More From: Combinatorial chemistry & high throughput screening
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