A Network Pharmacology Approach to Evaluate the Anticancer Mechanisms of Phytochemicals from Salvia urmiensis

Abstract

This study applied an integrated network pharmacology approach to explore the potential anticancer mechanisms of phytochemicals derived from Salvia urmiensis. Initially, the PharmMapper server was used to predict potential protein and gene targets for each ligand through pharmacophore-based mapping [1]. Subsequently, cancer-associated genes were obtained from the DisGeNET database, and a comparative analysis was conducted to identify overlapping genes between ligand targets and disease-related genes, offering insight into potential molecular interactions [2]. To better understand the interaction landscape, gene–protein interaction networks were constructed using Cytoscape, while protein–protein interaction (PPI) networks were generated via the STRING database. Key hub proteins with high connectivity including: MMP3, CASP7, NOS3, EGFR, ESR1, ESR2 and GSTP1 Were identified for downstream analysis. These core proteins were then subjected to functional enrichment analysis, including Gene Ontology (GO) and KEGG pathway mapping, using the DAVID platform. The enrichment results revealed several critical biological processes and signaling pathways potentially modulated by the phytochemicals. Overall, this study provides valuable insights into the molecular basis of the anticancer activity of Salvia urmiensis constituents and supports their potential application in cancer therapy.