Wuchty Stefan, Boltz Toni, Küçük-McGinty Hande
Department of Computer Science, University of Miami, Coral Gables, FL, USA.
Center of Computational Sciences, University of Miami, Coral Gables, FL, USA.
Proteomics. 2017 May;17(10):e1700056. doi: 10.1002/pmic.201700056. Epub 2017 May 2.
Focusing on the interactomes of Homo sapiens, Saccharomyces cerevisiae, and Escherichia coli, we investigated interactions between controlling proteins. In particular, we determined critical, intermittent, and redundant proteins based on their tendency to participate in minimum dominating sets. Independently of the organisms considered, we found that interactions that involved critical nodes had the most prominent effects on the topology of their corresponding networks. Furthermore, we observed that phosphorylation and regulatory events were considerably enriched when the corresponding transcription factors and kinases were critical proteins, while such interactions were depleted when they were redundant proteins. Moreover, interactions involving critical proteins were enriched with essential genes, disease genes, and drug targets, suggesting that such characteristics may be key for the detection of novel drug targets as well as assess their efficacy.
聚焦于人类、酿酒酵母和大肠杆菌的相互作用组，我们研究了调控蛋白之间的相互作用。具体而言，我们根据它们参与最小支配集的倾向来确定关键、间歇性和冗余蛋白。无论所考虑的生物体如何，我们发现涉及关键节点的相互作用对其相应网络的拓扑结构具有最显著的影响。此外，我们观察到当相应的转录因子和激酶是关键蛋白时，磷酸化和调控事件显著富集，而当它们是冗余蛋白时，此类相互作用则减少。此外，涉及关键蛋白的相互作用富含必需基因、疾病基因和药物靶点，这表明这些特征可能是检测新型药物靶点以及评估其疗效的关键。
