
pmid: 18790083
Deciphering the complex network structure is crucial in drug target identification. This study presents a framework incorporating graph theoretic and network decomposition methods to analyze system-level properties of the comprehensive map of the epidermal growth factor receptor (EGFR) signaling, which is a good candidate model system to study the general mechanisms of signal transduction. The graph theoretic analysis of the EGFR network indicates that it has small-world characteristics with scale-free topology. The employment of network decomposition analysis enlightened the system-level properties, such as network cross-talk, specific molecules in each pathway and participation of molecules in the network. Participating in a significant fraction of the fundamental paths connecting the ligands to the phenotypes, cofactor GTP and complex Gbeta/Ggamma were identified as "housekeeping" molecules, through which all pathways of EGFR network are cross-talking. c-Src-Shc complex is identified as important due to its role in all fundamental paths through tumorigenesis and being specific to this phenotype. Inhibitors of this complex may be good anti-cancer agents having very little or no effect on other phenotypes.
Epidermal growth factor receptor, Drug target, Health Informatics, Antineoplastic Agents, Signal transduction, Computer Science Applications, Neoplasm Proteins, Graph theory, ErbB Receptors, Drug Delivery Systems, Neoplasms, Tumorigenesis, Drug Discovery, Humans, Network decomposition analysis, Signal Transduction
Epidermal growth factor receptor, Drug target, Health Informatics, Antineoplastic Agents, Signal transduction, Computer Science Applications, Neoplasm Proteins, Graph theory, ErbB Receptors, Drug Delivery Systems, Neoplasms, Tumorigenesis, Drug Discovery, Humans, Network decomposition analysis, Signal Transduction
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