Network Pharmacology Prediction and Metabolomics Validation of the Novel Targets of Morus alba L. against High-Fat Diet-Induced Diabetes Mellitus in C57/6J Mice

Abstract

Diabetes mellitus (DM) is an endocrine-metabolic disorder that has limited approaches to treat effectively. Morus alba L., also known as mulberry, is a well-known medicinal plant, and its branch bark has shown hypoglycemic activity. It is rich in antioxidant and anti-inflammatory ingredients. In this study, we used metabolomics combined with network pharmacology to investigate the molecular mechanism and potential key targets of mulberry branch bark powder (MBBP) for treating DM. Serum metabolomics was performed to analyze the differences in metabolites and enrich metabolic pathways. Network pharmacology, based on systems biology tools, was applied to generate the pathway-target-compound network. Integrated analyses were then used to screen for key targets. To verify the obtained key targets, we used a molecular docking method and experimental validation. Our findings revealed that thirty-five endogenous metabolites contributed to the therapeutic impact of MBBP against DM. The analysis of 10 hub genes in the compound-target network partially supported the enrichment of metabolic pathways. Further analysis focused on two compounds (eugenol and mulberrofuran A) and three key targets (NOS2, MAOA, and CYP1A1). This study explores the active compounds of MBBP against DM and provides a novel perspective for improving DM treatment based on key targets.