Based on Network Pharmacology and Molecular Docking to Explore the Underlying Mechanism of Huangqi Gegen Decoction for Treating Diabetic Nephropathy.

Shanshan Ding,Weihao Wang,Hao Ma,Xujiao Song,Amin Tamadon

doi:10.1155/2021/9928282

Abstract

Background Huangqi Gegen decoction (HGD), a Chinese herb formula, has been widely used to treat diabetic nephropathy in China, while the pharmacological mechanisms are still unclear. Therefore, the present study aims to explore the underlying mechanism of HGD for treating diabetic nephropathy (DN). Materials and Methods Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), UniProt, and SwissTargetPrediction databases were used to search the active ingredients and potential targets of HGD. In addition, multiple disease-related databases were used to collect DN-related targets. Common targets of the protein-protein interaction (PPI) network were established using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the DAVID database. At last, AutoDockVina was used to conduct molecular docking verification for the core components and targets. Results A total of 27 active ingredients and 354 putative identified target genes were screened from HGD, of which 99 overlapped with the targets of DN and were considered potential therapeutic targets. Further analysis showed that the HGD activity of quercetin, formononetin, kaempferol, isorhamnetin, and beta-sitosterol ingredients is possible through VEGFA, IL6, TNF, AKT1, and TP53 targets involved in TNF, toll-like receptors, and MAPK-related pathways, which have anti-inflammatory, antiapoptosis, antioxidation, and autophagy effects, relieve renal fibrosis and renal cortex injury, and improve renal function, thus delaying the development of DN. The molecular docking results showed that quercetin, formononetin, kaempferol, isorhamnetin, beta-sitosterol had a good binding activity with VEGFA, IL6, TNF, AKT1, and TP53. Conclusion This study demonstrated that HGD might take part in the treatment of DN through multicomponent, multitarget, and multichannel combined action.

Highlights

Diabetic nephropathy (DN) is one of the most important microvascular complications of diabetes, accounting for about 20%–40% of all diabetic patients [1]
Network pharmacology combined with molecular docking can make up for one-sided and unsystematic research on the mechanism of drug therapy. erefore, this study explored the mechanism of Huangqi Gegen decoction (HGD) in the treatment of DN through network pharmacology method and molecular docking technology and provided new ideas for clinical application
Binding energy the core components of HGD had a strong binding activity with the AKT1 target. erefore, these results indicate that HGD can play a therapeutic role in DN by regulating oxidative stress and autophagy and counteracting hypoxia and other pathways

Summary

Introduction

Diabetic nephropathy (DN) is one of the most important microvascular complications of diabetes, accounting for about 20%–40% of all diabetic patients [1]. Huangqi Gegen decoction (HGD), derived from ancient books, has the effects of invigorating the spleen and replenishing Qi, nourishing Yin and clearing heat, invigorating body fluid, and relieving thirst. It can be used in hypertension and diabetes due to deficiency of both Qi and Yin. e whole prescription is composed of Astragalus membranaceus (Huangqi) and Pueraria (Gegen). Huangqi Gegen decoction (HGD), a Chinese herb formula, has been widely used to treat diabetic nephropathy in China, while the pharmacological mechanisms are still unclear. Further analysis showed that the HGD activity of quercetin, formononetin, kaempferol, isorhamnetin, and beta-sitosterol ingredients is possible through VEGFA, IL6, TNF, AKT1, and TP53 targets involved in TNF, toll-like receptors, and MAPK-related pathways, which have anti-inflammatory, antiapoptosis, antioxidation, and autophagy effects, relieve renal fibrosis and renal cortex injury, and improve renal function, delaying the development of DN

Methods

Results

Discussion

Conclusion