Insight into Shenqi Jiangtang Granule on the improved insulin sensitivity by integrating in silico and in vivo approaches.

Ethnopharmacological Relevance: Presently, insulin resistance has been a growing concern that urgently needs to be addressed, because it not only places patients at risk of developing type 2 diabetes mellitus but also results in metabolic syndrome and different aspects of cardiovascular diseases. Shenqi Jiangtang Granule (SJG) is a classic traditional Chinese medicine (TCM) prescription that is widely used to treat diabetes mellitus and its complications in clinical practice. While studies have revealed that SJG with multi-ingredients and multi-targets characteristics possesses potential anti-insulin resistance pharmacological properties, its mechanisms of action and molecular targets for the treatment of insulin resistance are still obscure, which prompt us to conduct an in-depth research.

Aim Of The Study: This study was purposed to uncover the pharmacological mechanism of SJG against insulin resistance through integrating network pharmacology and experimental validation.

Materials And Methods: The putative ingredients of SJG and its related targets were discerned from the TCMSP database. Subsequently, insulin resistance-associated targets were retrieved from GeneCard, OMIM, and GEO database. Compound-target, protein-protein interaction (PPI), and compound-target-pathway networks were established using Cytoscape software. GO and KEGG pathway analyses were performed to identify possible enrichment of genes with specific biological themes. Molecular docking was used to verify the correlation between the main active ingredients and hub targets. Optimal docking conformation was further analyzed by molecular dynamics (MD) simulation. Finally, the potential molecular mechanisms of SJG acting on insulin resistance, as predicted by the network pharmacology analyses, were validated experimentally in insulin-resistant rat model.

Results: 136 active compounds, 211 corresponding targets in addition to 1463 disease-related targets were collected, of which 94 intersection targets were obtained. 29 key targets including AKT1, VEGFA, IL-6, CASP3, and PTGS2 were identified through PPI network analysis. Hub module of PPI network was closely associated with inflammation. GO and KEGG analyses also revealed that inflammation-related pathways may be a central factor for SJG to modulate insulin resistance. Molecular docking test showed a good binding potency between primary active ingredients and core targets, and the binding mode of optimal docking conformation was stable in MD simulation. A rat model of insulin resistance was successfully induced by chronic high-fat diet (HFD) consumption. Through a series of in vivo studies, including HEC, ITT, and HOMA-IR measurement, it was revealed that SJG exhibited a beneficial effect on ameliorating insulin resistance, as demonstrated by a significant increase of GIR and a significant decrease of AUC and HOMA-IR index value. Further molecular biological analysis showed that SJG can decrease the mRNA expression level and serum concentration of inflammatory cytokines (TNF-α, IL-6, and IL-1β), along with suppressing the p-NFκB protein overexpression, indicating its anti-inflammatory activity. Also, it can contribute to the reversal of the impaired hepatic insulin signaling pathway, as evidenced by up-regulated protein expression of p-Akt and GLUT2.

Conclusions: Through in silico and in vivo approaches, the present study not only provides a unique insight into the possible mechanism of SJG in insulin resistance after successfully filtering out associated key target genes and signaling pathways, but also suggests a novel promising therapeutic strategy for curing insulin resistance.