Network pharmacology analysis of Chandraprabha Vati: A new hope for the treatment of Metabolic Syndrome

Abstract

Background

Drug research is increasingly using Network Pharmacology (NP) to tackle complex conditions like Metabolic Syndrome (MetS), which is characterized by obesity, hyperglycemia, and dyslipidemia. Single-action drugs are inadequate to treat MetS, which is marked by a range of complications including glucose intolerance, hyperlipidemia, mitochondrial dysfunction, and inflammation.

Objectives

To analyze Chandraprabha vati using Network Pharmacology to assess its potential in alleviating MetS-related complications.

Material and methods

The genes related to MetS, inflammation, and the target genes of the CPV components were identified using network pharmacology tools like DisgNET and BindingDB. Followed by mapping of the CPV target genes with the genes implicated in MetS and inflammation to identify putative potential targets. Gene ontology, pathway enrichment analysis, and STRING database were employed for further exploration. Furthermore, drug-target-protein interactions network were visualized using Cytoscape 3.9.1.

Results

The results showed that out of the 225 target genes of the CPV components, 33 overlapping and 19 non-overlapping genes could be potential targets for MetS. Similarly, 14 overlapping and 7 non-overlapping genes could be potential targets for inflammation. The CPV bioactives target genes were found to be involved in lipid and insulin homeostasis via several pathways revealed by the pathway analysis. The importance of CPV in treating MetS was supported by GO enrichment data; this could be due to its potential to influence pathways linked to metabolism, ER stress, mitochondrial dysfunction, oxidative stress, and inflammation.

Conclusions

These results offer a promising approach to developing treatment and repurposing CPV for complex conditions such as MetS.