Graph-theoretical Analysis of a Modeled Protein-protein Interaction Network in the RAS Signaling Pathway

The RAS signaling pathway is a fundamental regulator of cellular growth, proliferation, and survival. Dysregulation of this pathway is strongly implicated in cancer development, yet systematic strategies for identifying which pathway proteins represent the most promising therapeutic targets remain limited. The rationale of this study was to investigate the diversity of central proteins within the RAS signaling pathway and assess their functional significance in cancer biology. To achieve this, we modeled the human protein-protein interaction network as a metric space using a graph-theoretical framework. Shortest-path distances were computed to identify the most central proteins, which were then classified into functional zones. Proteins located in zone 1, representing the most connected zone, were cross-referenced with curated RAS pathway datasets. Functional enrichment analysis, oncogene/tumor suppressor evaluation, and cancer genome data integration were used to interpret biological roles and therapeutic potential. The results revealed that 95.2% of central RAS proteins are involved in signaling, with 59.5% classified as essential. Key proteins such as BCL2L1, RAF1, RHOA, MAP2K1, EGFR, CDC42, and ANGPT1 were identified as central players in processes including apoptosis resistance, metastasis, angiogenesis, and tumor progression. Several of these proteins also showed strong associations with established oncogenes and successful therapeutic targets. In conclusion, this study demonstrates that central proteins in the RAS signaling pathway exhibit functional diversity that underpins their importance in cancer progression. These findings provide a reproducible network-based workflow for identifying pathway-relevant molecular candidates and contribute to the development of more precise, pathway-oriented cancer therapies.