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Prediction of Protein-Protein Interactions from Secondary Structures in Binding Motifs Using the Statistic Method

机译:用统计方法预测二次结构的蛋白质 - 蛋白质相互作用

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Protein-protein interactions and their full network are crucial to understand biological function and disease occurrence. In respect of involvement of binding motifs and specific secondary structures in protein-protein interactions, we applied a statistical method to explore the frequency with which helices, sheets and disordered secondary structures appeared on protein-protein binding motif regions and tried to predict protein-protein interactions taking this frequency as a threshold. The results have shown that i ) on the average, helices and disordered structures constitute most of the binding regions (about 92%). ii ) for individual binding motif, the ratio may not be as significant as that in general cases. However, it is still greatly higher than that in random condition. This conclusion will be beneficial to protein-protein interaction prediction from a new orientation, secondary structures, instead of traditional ways of amino acid sequences and three-dimensional protein structures.
机译:蛋白质 - 蛋白质相互作用及其全网络对于了解生物学功能和疾病发生至关重要。关于蛋白质 - 蛋白质相互作用中的结合基序和特异性二次结构的参与,我们应用了一种统计方法,探讨了蛋白质 - 蛋白结合基质区域上出现的螺旋,片和无序的二次结构的频率,并试图预测蛋白质 - 蛋白质将此频率的交互作为阈值。结果表明I)在平均,螺旋和无序结构构成大部分结合区域(约92%)。 ii)对于个体结合基序,该比例可能不像一般情况一样重要。然而,它仍然大大高于随机条件。该结论将有利于来自新取向,二次结构的蛋白质 - 蛋白质相互作用预测,而不是氨基酸序列的传统方式和三维蛋白质结构。

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