Nguyen Thanh-Phuong, Caberlotto Laura, Morine Melissa J, Priami Corrado
The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068 Rovereto, Italy.
The Microsoft Research, University of Trento Centre for Computational Systems Biology (COSBI), Piazza Manifattura 1, 38068 Rovereto, Italy ; Department of Mathematics, University of Trento, Via Sommarive, 14-38123 Povo, Italy.
Biomed Res Int. 2014;2014:686505. doi: 10.1155/2014/686505. Epub 2014 Jan 16.
Despite significant advances in the study of the molecular mechanisms altered in the development and progression of neurodegenerative diseases (NDs), the etiology is still enigmatic and the distinctions between diseases are not always entirely clear. We present an efficient computational method based on protein-protein interaction network (PPI) to model the functional network of NDs. The aim of this work is fourfold: (i) reconstruction of a PPI network relating to the NDs, (ii) construction of an association network between diseases based on proximity in the disease PPI network, (iii) quantification of disease associations, and (iv) inference of potential molecular mechanism involved in the diseases. The functional links of diseases not only showed overlap with the traditional classification in clinical settings, but also offered new insight into connections between diseases with limited clinical overlap. To gain an expanded view of the molecular mechanisms involved in NDs, both direct and indirect connector proteins were investigated. The method uncovered molecular relationships that are in common apparently distinct diseases and provided important insight into the molecular networks implicated in disease pathogenesis. In particular, the current analysis highlighted the Toll-like receptor signaling pathway as a potential candidate pathway to be targeted by therapy in neurodegeneration.
尽管在神经退行性疾病(NDs)发生和发展过程中改变的分子机制研究方面取得了重大进展,但其病因仍然不明,而且疾病之间的区别也并非总是完全清晰。我们提出了一种基于蛋白质-蛋白质相互作用网络(PPI)的有效计算方法,用于对NDs的功能网络进行建模。这项工作的目标有四个:(i)重建与NDs相关的PPI网络,(ii)基于疾病PPI网络中的接近度构建疾病之间的关联网络,(iii)量化疾病关联,以及(iv)推断疾病中涉及的潜在分子机制。疾病的功能联系不仅与临床环境中的传统分类有重叠,而且还为临床重叠有限的疾病之间的联系提供了新的见解。为了更全面地了解NDs涉及的分子机制,我们研究了直接和间接连接蛋白。该方法揭示了明显不同疾病中共同存在的分子关系,并为疾病发病机制中涉及的分子网络提供了重要见解。特别是,当前的分析突出了Toll样受体信号通路作为神经退行性变治疗中潜在的靶向候选通路。