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PIPE:一种基于已知相互作用蛋白对之间反复出现的短多肽序列的蛋白质-蛋白质相互作用预测引擎。

PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs.

作者信息

Pitre Sylvain, Dehne Frank, Chan Albert, Cheetham Jim, Duong Alex, Emili Andrew, Gebbia Marinella, Greenblatt Jack, Jessulat Mathew, Krogan Nevan, Luo Xuemei, Golshani Ashkan

机构信息

School of Computer Science, Carleton University, Ottawa, Canada.

出版信息

BMC Bioinformatics. 2006 Jul 27;7:365. doi: 10.1186/1471-2105-7-365.

Abstract

BACKGROUND

Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions.

RESULTS

Here we explain the development and implementation of a novel Protein-Protein Interaction Prediction Engine termed PIPE. This tool is capable of predicting protein-protein interactions for any target pair of the yeast Saccharomyces cerevisiae proteins from their primary structure and without the need for any additional information or predictions about the proteins. PIPE showed a sensitivity of 61% for detecting any yeast protein interaction with 89% specificity and an overall accuracy of 75%. This rate of success is comparable to those associated with the most commonly used biochemical techniques. Using PIPE, we identified a novel interaction between YGL227W (vid30) and YMR135C (gid8) yeast proteins. This lead us to the identification of a novel yeast complex that here we term vid30 complex (vid30c). The observed interaction was confirmed by tandem affinity purification (TAP tag), verifying the ability of PIPE to predict novel protein-protein interactions. We then used PIPE analysis to investigate the internal architecture of vid30c. It appeared from PIPE analysis that vid30c may consist of a core and a secondary component. Generation of yeast gene deletion strains combined with TAP tagging analysis indicated that the deletion of a member of the core component interfered with the formation of vid30c, however, deletion of a member of the secondary component had little effect (if any) on the formation of vid30c. Also, PIPE can be used to analyse yeast proteins for which TAP tagging fails, thereby allowing us to predict protein interactions that are not included in genome-wide yeast TAP tagging projects.

CONCLUSION

PIPE analysis can predict yeast protein-protein interactions. Also, PIPE analysis can be used to study the internal architecture of yeast protein complexes. The data also suggests that a finite set of short polypeptide signals seem to be responsible for the majority of the yeast protein-protein interactions.

摘要

背景

在基因组时代之后,蛋白质相互作用网络的识别受到了广泛关注。目前用于检测蛋白质 - 蛋白质相互作用的生化方法都既耗时又费力。因此,越来越需要开发能够有效识别此类相互作用的计算工具。

结果

在此我们阐述了一种名为PIPE的新型蛋白质 - 蛋白质相互作用预测引擎的开发与实现。该工具能够从酿酒酵母蛋白质的一级结构预测任意目标对的蛋白质 - 蛋白质相互作用,且无需关于这些蛋白质的任何额外信息或预测。PIPE在检测任何酵母蛋白质相互作用时,灵敏度为61%,特异性为89%,总体准确率为75%。这一成功率与最常用的生化技术相当。使用PIPE,我们鉴定出酵母蛋白质YGL227W(vid30)和YMR135C(gid8)之间的一种新型相互作用。这使我们鉴定出一种新型酵母复合物,在此我们将其称为vid30复合物(vid30c)。通过串联亲和纯化(TAP标签)证实了所观察到的相互作用,验证了PIPE预测新型蛋白质 - 蛋白质相互作用的能力。然后我们使用PIPE分析来研究vid30c的内部结构。从PIPE分析来看,vid30c可能由一个核心和一个次要成分组成。酵母基因缺失菌株的产生与TAP标签分析表明,核心成分成员的缺失会干扰vid30c的形成,然而,次要成分成员的缺失对vid30c的形成几乎没有影响(如果有影响的话)。此外,PIPE可用于分析TAP标签失败的酵母蛋白质,从而使我们能够预测全基因组酵母TAP标签项目中未包含的蛋白质相互作用。

结论

PIPE分析可以预测酵母蛋白质 - 蛋白质相互作用。此外,PIPE分析可用于研究酵母蛋白质复合物的内部结构。数据还表明,有限的一组短多肽信号似乎是大多数酵母蛋白质 - 蛋白质相互作用的原因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cffb/1557541/6ac86723e3a4/1471-2105-7-365-1.jpg

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