Protein-protein interaction detection: methods and analysis.

International journal of proteomics Pub Date : 2014-01-01 Epub Date: 2014-02-17 DOI:10.1155/2014/147648
V Srinivasa Rao, K Srinivas, G N Sujini, G N Sunand Kumar
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引用次数: 515

Abstract

Protein-protein interaction plays key role in predicting the protein function of target protein and drug ability of molecules. The majority of genes and proteins realize resulting phenotype functions as a set of interactions. The in vitro and in vivo methods like affinity purification, Y2H (yeast 2 hybrid), TAP (tandem affinity purification), and so forth have their own limitations like cost, time, and so forth, and the resultant data sets are noisy and have more false positives to annotate the function of drug molecules. Thus, in silico methods which include sequence-based approaches, structure-based approaches, chromosome proximity, gene fusion, in silico 2 hybrid, phylogenetic tree, phylogenetic profile, and gene expression-based approaches were developed. Elucidation of protein interaction networks also contributes greatly to the analysis of signal transduction pathways. Recent developments have also led to the construction of networks having all the protein-protein interactions using computational methods for signaling pathways and protein complex identification in specific diseases.

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蛋白质-蛋白质相互作用检测:方法与分析。
蛋白质-蛋白质相互作用在预测靶蛋白的蛋白质功能和分子的药物能力方面起着关键作用。大多数基因和蛋白质是通过一系列相互作用来实现表型功能的。亲和纯化、Y2H(酵母2杂交)、TAP(串联亲和纯化)等体外和体内方法存在成本、时间等方面的局限性,所得数据集有噪声,对药物分子功能的注解存在较多假阳性。因此,计算机方法包括基于序列的方法、基于结构的方法、染色体接近、基因融合、计算机2杂交、系统发育树、系统发育谱和基于基因表达的方法。蛋白质相互作用网络的阐明也有助于信号转导途径的分析。最近的发展也导致了网络的构建,利用信号通路和特定疾病中蛋白质复合物识别的计算方法,具有所有蛋白质-蛋白质相互作用。
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