Durmuş Tekir Saliha, Yalçin Arga Kazim, Ulgen Kutlu O
Department of Chemical Engineering, Boğaziçi University, 34342 Bebek-Istanbul, Turkey.
J Biomed Inform. 2009 Apr;42(2):228-36. doi: 10.1016/j.jbi.2008.08.008. Epub 2008 Aug 26.
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.
破译复杂的网络结构对于药物靶点识别至关重要。本研究提出了一个结合图论和网络分解方法的框架，用于分析表皮生长因子受体（EGFR）信号通路综合图谱的系统级特性，EGFR信号通路是研究信号转导一般机制的良好候选模型系统。对EGFR网络的图论分析表明，它具有无标度拓扑的小世界特征。网络分解分析的应用揭示了系统级特性，如网络串扰、各通路中的特定分子以及分子在网络中的参与情况。辅因子GTP和复合物Gbeta/Ggamma参与了连接配体与表型的大部分基本通路，被确定为“管家”分子，EGFR网络的所有通路都通过它们进行串扰。c-Src-Shc复合物因其在所有通过肿瘤发生的基本通路中的作用以及对该表型的特异性而被确定为重要分子。该复合物的抑制剂可能是对其他表型影响很小或没有影响的良好抗癌药物。
