Identification of potential bioactive compounds and mechanisms of GegenQinlian decoction on improving insulin resistance in adipose, liver, and muscle tissue by integrating system pharmacology and bioinformatics analysis

Abstract

Ethnopharmacological relevanceGegenQinlian Decoction (GQD), a classical formula in traditional Chinese medicine, is widely used in the treatment of diabetes. While studies have demonstrated that GQD is an efficacious treatment for insulin resistance (IR) in type 2 diabetes mellitus (T2DM), the potential bioactive compounds and mechanisms remain unclear. Aim of the studyTo further investigate the potential bioactive compounds, targets, and pathways of GQD on improving IR in T2DM for adipose, liver, and muscle tissue using an integrated strategy of system pharmacology and bioinformatics analysis. Materials and methodsWe screened the candidate compounds and targets of GQD and identified IR-associated differentially expressed genes (DEGs) of adipose, liver, and muscle tissue, respectively. Then the intersecting target genes between candidate targets and DEGs were used for “GQD-compounds-targets-tissue” network construction in each type of tissue. The top 10 bioactive compounds acting on each type of tissue were intersected and consequently identified as potential bioactive compounds of GQD. Furthermore, pathway enrichment, protein-protein interaction (PPI) network construction, and hub target identification were performed based on the targets of GQD and the targets of quercetin in each type of tissue, respectively. Finally, to further confirm the role of quercetin, we intersected the hub targets of quercetin and the hub targets of GQD, and the pathways were intersected as well. Results132 compounds and 119 potential targets of these compounds were obtained. 1,765, 3,206, and 3594 DEGs were identified between IR and insulin sensitivity (IS) tissue in adipose, liver, and muscle, respectively. There were 21, 23, 45 targets and 103, 73, 123 compounds in the “GQD-compounds-targets-tissue” network of adipose, liver, and muscle tissue, respectively. Then compounds such as quercetin, kaempferol, baicalein, wogonin, isorhamnetin, beta-sitosterol and licochalcone A, were identified as the potential bioactive compounds of GQD, and quercetin had the highest degree among the compounds. Moreover, based on the targets of GQD, hub targets like PPARG, RELA, EGFR, CASP3, VEGFA, AR, ESR1 and CCND1, and signaling pathways such as insulin signaling pathway, endocrine resistance, TNF signaling pathway, PI3K-Akt signaling pathway, AMPK signaling pathway, MAPK signaling pathway, NF-κB signaling pathway, HIF-1 signaling pathway, apoptosis, and VEGF signaling pathway, were filtered out as the underlying mechanisms of GQD on improving diabetic IR. In addition, the hub targets and pathways of quercetin coincided with most of the hub targets and pathways of GQD in each type of tissue, respectively, suggesting that quercetin may be a potential representative compound of GQD. ConclusionsOur analysis identifies the potential bioactive compounds, targets, and pathways of GQD on improving IR in T2DM for adipose, liver, and muscle tissue, which shows the characteristics of multi-compounds, multi-targets, multi-pathways, and multi-mechanisms of GQD and lays a solid foundation for further experimental research and clinical application.