Computational identification of protein-protein interactions in rice based on the predicted rice interactome network.
Computational identification of protein-protein interactions in rice based on the predicted rice interactome network.
复制标题
基于预测的水稻相互作用组网络的水稻中蛋白质-蛋白质相互作用的计算鉴定
DOI：
10.1016/s1672-0229(11)60016-8
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发表时间：
2011-10
影响因子：
9.5
通讯作者：
Chen, Ming
中科院分区：
文献类型：
--
作者：
Zhu, Pengcheng;Gu, Haibin;Jiao, Yinming;Huang, Donglin;Chen, Ming
植物蛋白质-蛋白质相互作用网络还没有被大规模的实验所证实。为了更好地了解水稻中蛋白质的相互作用，预测的水稻互作组网络(Prin；http://bis.zju.edu.cn/prin/))提供了76,585个预测的相互作用，涉及5,049个大米蛋白质。通过绘制水稻基因组特征图(GO注释、亚细胞定位预测和基因表达)，我们发现一个注释良好且具有生物学意义的网络足够丰富，足以捕捉到高等生物系统中许多重要的功能联系，如途径和生物过程。此外，我们以含有MADS-box结构域的蛋白质和昼夜节律信号通路为例，证明了功能蛋白质复合体和生物通路可以在我们预测的网络中有效地扩展。Prin中扩展的分子网络极大地提高了这些分析整合现有知识的能力，并为基因和基因网络的功能和协调提供了新的见解。
Plant protein-protein interaction networks have not been identified by large-scale experiments. In order to better understand the protein interactions in rice, the Predicted Rice Interactome Network (PRIN; http://bis.zju.edu.cn/prin/) presented 76,585 predicted interactions involving 5,049 rice proteins. After mapping genomic features of rice (GO annotation, subcellular localization prediction, and gene expression), we found that a well-annotated and biologically significant network is rich enough to capture many significant functional linkages within higher-order biological systems, such as pathways and biological processes. Furthermore, we took MADS-box domain-containing proteins and circadian rhythm signaling pathways as examples to demonstrate that functional protein complexes and biological pathways could be effectively expanded in our predicted network. The expanded molecular network in PRIN has considerably improved the capability of these analyses to integrate existing knowledge and provide novel insights into the function and coordination of genes and gene networks.