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Short Co-occurring Polypeptide Regions Can Predict Global Protein Interaction Maps

机译:短时共生多肽区域可以预测全球蛋白质相互作用图。

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A goal of the post-genomics era has been to elucidate a detailed global map of protein-protein interactions (PPIs) within a cell. Here, we show that the presence of co-occurring short polypeptide sequences between interacting protein partners appears to be conserved across different organisms. We present an algorithm to automatically generate PPI prediction method parameters for various organisms and illustrate that global PPIs can be predicted from previously reported PPIs within the same or a different organism using protein primary sequences. The PPI prediction code is further accelerated through the use of parallel multi-core programming, which improves its usability for large scale or proteome-wide PPI prediction. We predict and analyze hundreds of novel human PPIs, experimentally confirm protein functions and importantly predict the first genome-wide PPI maps for S. pombe (~9,000 PPIs) and C. elegans (~37,500 PPIs).. ? 2012 Macmillan Publishers Limited. All rights reserved
机译:后基因组学时代的目标是阐明细胞内蛋白质-蛋白质相互作用(PPI)的详细全局图。在这里,我们显示了相互作用的蛋白质伴侣之间共存的短多肽序列的存在似乎在不同生物之间是保守的。我们提出了一种算法,可以自动生成各种生物的PPI预测方法参数,并说明可以使用蛋白质一级序列从相同或不同生物中先前报告的PPI预测全局PPI。通过使用并行多核编程,可以进一步加速PPI预测代码,从而提高了其在大规模或蛋白质组范围内PPI预测的可用性。我们预测并分析了数百种新型人类PPI,通过实验确定了蛋白质功能,并重要地预测了粟酒裂殖酵母(〜9,000 PPI)和秀丽隐杆线虫(〜37,500 PPI)的首个全基因组PPI图。 2012 Macmillan Publishers Limited。版权所有

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