Molecular mechanism of the effect of gegen qinlian decoction on type 2 diabetes mellitus based on network pharmacology and molecular docking

Abstract

Gegen qinlian decoction (GGQLD) is a Traditional Chinese Medicine formula comprising four herbal medicines. It is commonly used to treat bacterial dysentery in the past. Modern research has repositioned this decoction and applied it to treat type 2 diabetes mellitus (T2DM) and has achieved good results. However, the molecular mechanism of GGQLD in treating T2DM is still not fully known. Hence, this study was designed to explore the effective components and potential mechanism of GGQLD in the treatment of T2DM by using network pharmacology and molecular docking technology. The herb-compound-target interaction network was constructed by retrieving and screening of active components in different herbs in GGQLD and corresponding T2DM-related target genes across multiple databases. Subsequently, STRING and Cytoscape were applied to analyze and construct PPI network. Then, GO and KEGG pathway enrichment analysis were performed to investigate biological processes and pathways involved in GGQLD. The differentially expressed analysis was used to verify whether the expression of key target genes in T2DM and non-T2DM samples was statistically significant. Finally, the binding capacity between active components and key targets was validated by molecular docking using AutoDock4. The results shows that there are 60 active components involved in 100 T2DM-related targets that are identified in GGQLD formula. PPI networks were constructed and 10 key targets (IL1B, EGFR, VEGFA, IL6, JUN, TP53, MAPK3, AKT1, CASP3 and TNF) were obtained after topological analysis. Further, GO and KEGG analysis showed that GGQLD may play an important role in treating T2DM and its complications by synergistically regulating many biological processes and pathways involved in inflammatory response, hypoxia reaction, angiogenesis, cell growth, apoptosis, senescence, and biological processes mediated by PI3K-AKT, HIF-1, EGFR signaling pathways. Gene expression microarray data analysis showed that the expression of IL1B, IL6, EGFR, TP53, VEGFA, and JUN in T2DM samples were significantly different from those in normal controls. 4 high-affinity active components of GGQLD binding with the 10 key targets, including kaempferol, quercetin, naringenin and beta-sitosterol have been identified by molecular docking. Furthermore, the molecular dynamics simulation analysis by GROMACS showed the stability of the compound-protein binding complex. Our research preliminarily revealed the material basis and relevant mechanisms of GGQLD in treating T2DM and its complications. The prediction results might facilitate the development of GGQLD or its active compounds as alternative therapy for T2DM, and provide support for further study and experimental validation.