Background: Shegan Mixture (SGM) is a traditional Chinese medicine that has anti-inflammatory and therapeutic effects on asthma. However, its active ingredients and combined action mechanism have not been fully elucidated so far. The purpose of this study was to screen the effective ingredients and targets and elucidate the synergistic action mechanism of SGM in asthma mice using the network pharmacological approach.
Methods: A mouse model of asthma model was used in this study. Mice were orally administered SGM at three doses for 4 weeks and the effect of SGM on asthma was evaluated. The active ingredients and their targets of SGM were identified by searching databases, such as Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). The main active ingredients were selected with parameters OB and DL. The synergistic action mechanisms of SGM in asthma were studied through key active ingredient-target interaction network and verified using surface plasmon resonance assay (SPR).
Results: SGM exerts anti-asthmatic effects by reducing lung tissue damage and inflammatory factors (IFN-γ, IL-4, IL-5, and IL-13) in asthmatic mice. Twenty ingredients and 45 related proteins were selected as potential nodes using enrichment analysis and network analysis. Inflammation and smooth muscle regulation-related pathways were considered to be the main pharmacological mechanisms of SGM in the treatment of asthma. Especially, 5 molecule-target pairs (including 3 ingredients and 4 proteins) were well docked with each other and the SPR assay revealed that glabridin-PTGS2 had good binding with 44.5 μM Kd value.
Conclusion: SGM exerts the synergistic anti-asthma effects by virtue of reducing lung-tissue damage and inflammatory factors in asthmatic mice, which explains the theoretical basis for the traditional Chinese medicine, SGM, to treat asthma. Our study thus sheds light on a variety of options including Chinese medicine that could potentially be used in the clinical treatment of asthma.
Keywords: Shegan mixture, asthma, network pharmacology, surface plasmon resonance, traditional Chinese medicine