Yang Lei, Hao Dapeng, Wang Jizhe, Xing Xudong, Lv Yingli, Zuo Yongchun, Jiang Wei
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, PR China.
Mol Biosyst. 2015 May;11(5):1360-9. doi: 10.1039/c5mb00124b.
Acquiring comprehensive knowledge of protein in various subcellular localizations is one of the fundamental goals in cell biology and proteomics. Although recent large-scale experimental and proteomics studies of S. cerevisiae protein subcellular localizations are archived in various databases, only a few studies use a systems biology approach to characterize S. cerevisiae proteins at a subcellular localization level. Based on the topological properties and biological properties of S. cerevisiae proteins, we have compared, contrasted and analyzed the statistical properties across eight different subcellular localizations. Significant differences are found in all topological properties and biological properties among eight protein categories. Network topology analysis indicates that the nuclear proteins differ from the other seven protein categories, and tend to have the most important topological properties and play an important role in the network, including the highest degree, core number, and betweenness centrality. In the light of the above, we hope these findings presented in this study may provide important help for protein subcellular localization prediction in S. cerevisiae and provide many new insights for understanding the proteins directly from subcellular localizations.
获取关于各种亚细胞定位中蛋白质的全面知识是细胞生物学和蛋白质组学的基本目标之一。尽管最近关于酿酒酵母蛋白质亚细胞定位的大规模实验和蛋白质组学研究已存档于各种数据库中，但只有少数研究采用系统生物学方法在亚细胞定位水平上对酿酒酵母蛋白质进行表征。基于酿酒酵母蛋白质的拓扑特性和生物学特性，我们对八个不同亚细胞定位的统计特性进行了比较、对比和分析。在八个蛋白质类别之间的所有拓扑特性和生物学特性中都发现了显著差异。网络拓扑分析表明，核蛋白与其他七个蛋白质类别不同，并且倾向于具有最重要的拓扑特性并在网络中发挥重要作用，包括最高的度、核心数和介数中心性。鉴于上述情况，我们希望本研究中呈现的这些发现可能为酿酒酵母中的蛋白质亚细胞定位预测提供重要帮助，并为直接从亚细胞定位理解蛋白质提供许多新的见解。
