Construction and analysis of the interactome of eugenol to identify the modular proteins and their role in cancer

Cancer is a disease resulting from abnormalities in complex biological networks. Rather than a single target, many potential drugs target multiple pathways through protein modulation. This leads to the motivation to develop methods that help to predict drug interactions in complex networks accurately. Eugenol, a phenylpropanoid, is used for the study. It has been found that eugenol is a drugable molecule that is effective in treating cancer. We have executed a computational platform that combines network pharmacology and systems biology to unravel the molecular mechanisms of the complex disease cancer. The primary PPI network was retrieved using the PubChem, CTD and STITCH databases and the interactome was constructed using STRING and analyzed using the Cytoscape tool. The interactome is simplified using MCODE. MCODE reduces the interactome to densely connected regions based on its topology. We identified RBL1, CXCL11, MVK, ELANE and FBXO11 as the top potential drug targets that may provide novel insights into drug discovery. The functional and pathway enrichment analysis of the top MCODE modules was performed using the PANTHER and DAVID databases respectively. The expression analysis of hub genes was carried out using a Kaplan-Meier plotter. These genes may serve as potential biomarkers to treat cancer.