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Highly precise protein-protein interaction prediction based on consensus between template-based and de novo docking methods

机译:基于模板对接和从头对接方法的共识的高精度蛋白质相互作用预测

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Background Elucidation of protein-protein interaction (PPI) networks is important for understanding disease mechanisms and for drug discovery. Tertiary-structure-based in silico PPI prediction methods have been developed with two typical approaches: a method based on template matching with known protein structures and a method based on de novo protein docking. However, the template-based method has a narrow applicable range because of its use of template information, and the de novo docking based method does not have good prediction performance. In addition, both of these in silico prediction methods have insufficient precision, and require validation of the predicted PPIs by biological experiments, leading to considerable expenditure; therefore, PPI prediction methods with greater precision are needed. Results We have proposed a new structure-based PPI prediction method by combining template-based prediction and de novo docking prediction. When we applied the method to the human apoptosis signaling pathway, we obtained a precision value of 0.333, which is higher than that achieved using conventional methods (0.231 for PRISM, a template-based method, and 0.145 for MEGADOCK, a non-template-based method), while maintaining an F-measure value (0.285) comparable to that obtained using conventional methods (0.296 for PRISM, and 0.220 for MEGADOCK). Conclusions Our consensus method successfully predicted a PPI network with greater precision than conventional templateon-template methods, which may thus reduce the cost of validation by laboratory experiments for confirming novel PPIs from predicted PPIs. Therefore, our method may serve as an aid for promoting interactome analysis.
机译:背景技术阐明蛋白质间相互作用(PPI)网络对于理解疾病机理和药物发现很重要。基于三级结构的计算机PPI预测方法已经开发出两种典型方法:基于与已知蛋白质结构匹配的模板的方法和基于从头蛋白质对接的方法。但是,基于模板的方法由于使用模板信息而具有较窄的适用范围,并且基于从头对接的方法不具有良好的预测性能。另外,这两种计算机模拟预测方法的精度均不足,并且需要通过生物学实验来验证预测的PPI,从而导致相当大的支出。因此,需要精度更高的PPI预测方法。结果我们结合了基于模板的预测和从头对接预测,提出了一种新的基于结构的PPI预测方法。当我们将该方法应用于人类凋亡信号通路时,我们获得的精确度值为0.333,高于使用常规方法所获得的精确度(PRISM为基于模板的方法为0.231,MEGADOCK为非模板的方法为0.145。 ),同时保持与传统方法(PRISM为0.296,MEGADOCK为0.220)相当的F测量值(0.285)。结论我们的共识方法成功地预测了PPI网络,其精度要高于传统的模板/非模板方法,因此可以减少通过实验室实验从预测的PPI确认新的PPI进行验证的成本。因此,我们的方法可能有助于促进相互作用组分析。

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