A Study on the Mechanism of Milkvetch Root in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

Chunli Piao; Qi Zhang; De Jin; Li Wang; Cheng Tang; Naiwen Zhang; Fengmei Lian; Xiaolin Tong

doi:10.1155/2020/6754761

A Study on the Mechanism of Milkvetch Root in the Treatment of Diabetic Nephropathy Based on Network Pharmacology

Evid Based Complement Alternat Med. 2020 Oct 31:2020:6754761. doi: 10.1155/2020/6754761. eCollection 2020.

Authors

Chunli Piao¹, Qi Zhang², De Jin³, Li Wang¹, Cheng Tang¹, Naiwen Zhang¹, Fengmei Lian³, Xiaolin Tong³

Affiliations

¹ Shenzhen Hospital, Guangzhou University of Chinese Medicine (Futian), Shenzhen 518000, Guangdong, China.
² Changchun University of Chinese Medicine, Changchun 130000, Jilin, China.
³ Guang'anmen Hospital, China Academy of Chinese Medical Science, Beijing 100000, China.

Abstract

Diabetic nephropathy (DN) is one of the most common complications of diabetes mellitus. Owing to its complicated pathogenesis, no satisfactory treatment strategies for DN are available. Milkvetch Root is a common traditional Chinese medicine (TCM) and has been extensively used to treat DN in clinical practice in China for many years. However, due to the complexity of botanical ingredients, the exact pharmacological mechanism of Milkvetch Root in treating DN has not been completely elucidated. The aim of this study was to explore the active components and potential mechanism of Milkvetch Root by using a systems pharmacology approach. First, the components and targets of Milkvetch Root were analyzed by using the Traditional Chinese Medicine Systems Pharmacology database. We found the common targets of Milkvetch Root and DN constructed a protein-protein interaction (PPI) network using STRING and screened the key targets via topological analysis. Enrichment of Gene Ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed. Subsequently, major hubs were identified and imported to the Database for Annotation, Visualization and Integrated Discovery for pathway enrichment analysis. The binding activity and targets of the active components of Milkvetch Root were verified by using the molecular docking software SYBYL. Finally, we found 20 active components in Milkvetch Root. Moreover, the enrichment analysis of GO and KEGG pathways suggested that AGE-RAGE signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, and TNF signaling pathway might be the key pathways for the treatment of DN; more importantly, 10 putative targets of Milkvetch Root (AKT1, VEGFA, IL-6, PPARG, CCL2, NOS3, SERPINE1, CRP, ICAM1, and SLC2A) were identified to be of great significance in regulating these biological processes and pathways. This study provides an important scientific basis for further elucidating the mechanism of Milkvetch Root in treating DN.