Network pharmacology and GEO database-based analysis of Sini powder in the prevention of depression among shift workers

Abstract

It has been estimated that approximately 20% of employed adults worldwide are required to undertake shift work, which has led to severe public health decline and depression. Sini powder (SNP) has been shown to be a promising medicine. However, the effectiveness and mechanism of reducing the risk of depression for shift workers are still unclear. Thus, network pharmacological analysis and gene expression profiling were introduced to reveal the mechanism of SNP in the prevention of depression. First, five databases were used to collect the chemical compounds of SNP, and absorption, distribution, metabolism, and excretion (ADME) properties were selected to identified high-quality compounds. Second, the targets of compounds were obtained by BATMAN-TCM. And the differentially expressed genes associated with depression among shift workers were obtained using gene expression profiling (GSE98793, GSE122541). Subsequently, key targets were screened out with a protein–protein interaction (PPI) network by String. Furthermore, functional enrichment was carried out by Metascape. Molecular docking was introduced to verify the interaction between core targets and compounds. SNP reduced the risk of depression by regulating ESR2, GPER1, TNF and APOE through the estrogen pathway and NOD-like receptor signaling pathway. This study provides a scientific basis for further investigating the mechanism by which SNP prevents depression and reduces the risk of depression for shift workers.

Keywords

• depression
• circadian rhythm
• shift worker
• traditional chinese medicine
• sini powder
• molecular mechanism