Identification of hub genes and candidate herbal treatment in obesity through integrated bioinformatic analysis and reverse network pharmacology

Abstract

Obesity is a worldwide epidemic disease that increases the risk of various metabolic disorders. However, in the absence of ideal drugs for obesity, Chinese herbs and other natural materials have been explored for their potential obesity treatment and low-side effects. The focus of this research was to use bioinformatics and reverse network pharmacology to discover possible therapy and treatment targets for obesity. We identified differentially expressed genes (DEGs) of adipose tissue after weight-loss by analyzing the five expression profiles of the GEO database (GSE103766, GSE35411, GSE112307, GSE43471, and GSE35710). Protein–Protein Interaction (PPI) network was performed with the STRING, and the 27 hub genes were identified with the MCODE. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed several biological features and potential mechanisms of these hub genes. Subsequently, the TCMSP platform was used to identify potential therapeutic herbs targeting hub genes. The top 10 key potential Chinese herbs were found and annotated with Chinese pharmaceutical properties (CMPs). Finally, the Herbs-Ingredient-Target Network and Herb-Taste-Meridian Tropism Network were constructed using Cytoscape to elucidate their complex relationship. Our outputs could provide new insights into strategies for treating obesity and screening targeted drugs.