Vinayagam Arunachalam, Gibson Travis E, Lee Ho-Joon, Yilmazel Bahar, Roesel Charles, Hu Yanhui, Kwon Young, Sharma Amitabh, Liu Yang-Yu, Perrimon Norbert, Barabási Albert-László
Department of Genetics, Harvard Medical School, Boston, MA 02115;
Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115;
Proc Natl Acad Sci U S A. 2016 May 3;113(18):4976-81. doi: 10.1073/pnas.1603992113. Epub 2016 Apr 18.
The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.
蛋白质-蛋白质相互作用(PPI)网络对于细胞信息处理和决策至关重要。在合适的输入条件下,PPI网络驱动细胞实现多种功能结果,如细胞增殖或细胞死亡。在此,我们对一个包含6339个蛋白质和34813个相互作用的大型人类有向PPI网络的结构可控性进行了表征。该网络使我们能够将蛋白质分类为“不可或缺的”、“中性的”或“可省去的”,这与去除该蛋白质后网络中驱动节点数量的增加、无影响或减少相关。我们发现PPI网络中21%的蛋白质是不可或缺的。有趣的是,这些不可或缺的蛋白质是致病突变、人类病毒和药物的主要靶点,这表明改变网络的控制特性对于健康状态和疾病状态之间的转变至关重要。此外,对1547名癌症患者的拷贝数变异数据进行分析发现,在九种不同癌症中经常扩增或缺失的56个基因是不可或缺的。在这56个基因中,其中46个基因以前未与癌症相关联。这表明可控性分析在识别新型疾病基因和潜在药物靶点方面非常有用。