An Integrated Approach Based on Network Pharmacology Combined with Experimental Verification Reveals AMPK/PI3K/Akt Signaling is an Important Way for the Anti-Type 2 Diabetic Activity of Silkworm Excrement

OBJECTIVE: This study was aimed to investigate the potential active components, targets and mechanisms of silkworm excrement (SE) in the treatment of type 2 diabetes mellitus (T(2)D) based on THE network pharmacology combined with experimental verification. METHODS: Firstly, the inhibitory effects of SE on α-glucosidase were measured in vitro. Then, the potential active components and potential targets of SE and the targets of T(2)D were collected and screened using bioinformatics databases. Then, the R language, Cytoscape, Perl software were used to screen and visualize important components, targets, biological processes and signaling pathways. Finally, the predicted results by network pharmacology were verified via glucose absorption assay, oil red O staining assay and Western blot assay. RESULTS: Our results showed SE effectively inhibited the activities of α-glucosidase. The results of network pharmacology suggested there were 33 potential active ingredients and 42 potential targets in SE. The molecular pathways of SE against T(2)D were further predicted, including response to insulin-like growth factor receptor binding, protein serine/threonine kinase activity, and MAP kinase activity. KEGG pathway analyses predicted potential targets were involved in multiple signaling pathways, such as insulin signaling pathway, insulin resistance pathway and AMPK signaling pathway. In IR HepG2 cells, SE treatments increased glucose consumption and decreased lipogenesis. The insulin resistance (IR)-related AMPK/PI3K/AKT signaling was further studied and the results showed SE could significantly up-regulate the phosphorylation levels of AMPK, PI3K, and Akt proteins in IR-HepG2 cells. CONCLUSION: Our results suggested AMPK/PI3K/Akt signaling is an important way for the anti-type 2 diabetic activity of silkworm excrement by using an integrated approach based on network pharmacology combined with experimental verification.