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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >IN SILICO SCREENING OF PROTEIN-PROTEININTERACTIONS WITH ALL-TO-ALL RIGIDDOCKING AND CLUSTERING: ANAPPLICATION TO PATHWAY ANALYSIS
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IN SILICO SCREENING OF PROTEIN-PROTEININTERACTIONS WITH ALL-TO-ALL RIGIDDOCKING AND CLUSTERING: ANAPPLICATION TO PATHWAY ANALYSIS

机译:在使用蛋白质对蛋白质的相互作用中进行全方位的刚性对接和聚类:在路径分析中的应用

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We propose a computational screening system of protein-protein interactions using ter-tiary structure data. Our system combines all-to-all protein docking and clustering tofind interacting protein pairs. We tuned our prediction system by applying variousparameters and clustering algorithms and succeeded in outperforming previous meth-ods. This method was also applied to a biological pathway estimation problem to showits use in network level analysis. The structural data were collected from the ProteinData Bank, PDB. Then all-to-all docking among target protein structures was conductedusing a conventional protein-protein docking software package, ZDOCK. The highest-ranked 2000 decoys were clustered based on structural similarity among the predicteddocking forms. The features of generated clusters were analyzed to estimate the bio-logical relevance of protein-protein interactions. Our system achieves a best F-measurevalue of 0.43 when applied to a subset of general protein-protein docking benchmarkdata. The same system was applied to protein data in a bacterial chemotaxis pathway,utilizing essentially the same parameter set as the benchmark data. We obtained 0.45for the F-measure value. The proposed approach to computational PPI detection is apromising methodology for mediating between structural studies and systems biologyby utilizing cumulative protein structure data for pathway analysis.
机译:我们提出了使用三级结构数据的蛋白质-蛋白质相互作用的计算筛选系统。我们的系统结合了所有蛋白质的对接和聚类,以找到相互作用的蛋白质对。我们通过应用各种参数和聚类算法对预测系统进行了调整,并成功超越了以前的方法。该方法还应用于生物途径估计问题,以证明其在网络级分析中的应用。结构数据是从ProteinData Bank,PDB收集的。然后使用常规的蛋白质-蛋白质对接软件包ZDOCK进行目标蛋白质结构之间的全部对接。根据预测的对接形式之间的结构相似性,对排名最高的2000个诱饵进行了聚类。分析了产生的簇的特征以估计蛋白质-蛋白质相互作用的生物学相关性。当将我们的系统应用于一般蛋白质-蛋白质对接基准数据的子集时,其最佳F测量值达到0.43。利用与基准数据基本相同的参数集,将同一系统应用于细菌趋化途径中的蛋白质数据。 F测量值得到0.45。提出的计算PPI检测方法是一种有前途的方法,可通过利用累积的蛋白质结构数据进行途径分析来在结构研究和系统生物学之间进行调节。

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