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细菌中蛋白质相互作用图谱的预测、评估与验证。

Prediction, assessment and validation of protein interaction maps in bacteria.

作者信息

Wojcik Jérôme, Boneca Ivo G, Legrain Pierre

机构信息

Hybrigenics, SA, 3-5 impasse Reille, Paris, France.

出版信息

J Mol Biol. 2002 Nov 1;323(4):763-70. doi: 10.1016/s0022-2836(02)01009-4.

Abstract

High-throughput proteomics technologies, especially the yeast two-hybrid system, produce large volumes of protein-protein interaction data organized in networks. The complete sequencing of many genomes raises questions about the extent to which such networks can be transferred between organisms. We attempted to answer this question using the experimentally derived Helicobacter pylori interaction map and the recently described interacting domain profile pair (IDPP) method to predict a virtual map for Escherichia coli. The extensive literature concerning E.coli was used to assess all predicted interactions and to validate the IDPP method, which clusters protein domains by sequence and connectivity similarities. The IDPP method has a much better heuristic value than methods solely based on protein homology. The IDPP method was further applied to Campylobacter jejuni to generate a virtual interaction map. An in-depth comparison of the chemotaxis pathways predicted in E.coli and C.jejuni led to the proposition of new functional assignments. Finally, the prediction of protein-protein interaction maps across organisms enabled us to validate some of the interactions on the original experimental map.

摘要

高通量蛋白质组学技术,尤其是酵母双杂交系统,产生了大量以网络形式组织的蛋白质-蛋白质相互作用数据。许多基因组的全序列测定引发了关于此类网络在不同生物体之间可转移程度的问题。我们试图利用实验得出的幽门螺杆菌相互作用图谱和最近描述的相互作用结构域谱对(IDPP)方法来预测大肠杆菌的虚拟图谱,以回答这个问题。利用关于大肠杆菌的大量文献来评估所有预测的相互作用,并验证IDPP方法,该方法通过序列和连接相似性对蛋白质结构域进行聚类。IDPP方法比仅基于蛋白质同源性的方法具有更好的启发价值。IDPP方法进一步应用于空肠弯曲菌以生成虚拟相互作用图谱。对大肠杆菌和空肠弯曲菌中预测的趋化途径进行深入比较,提出了新的功能分配。最后,跨生物体的蛋白质-蛋白质相互作用图谱预测使我们能够验证原始实验图谱上的一些相互作用。

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