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首页> 外文期刊>BMC Genomics >A generalized approach to predicting protein-protein interactions between virus and host
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A generalized approach to predicting protein-protein interactions between virus and host

机译：预测病毒与宿主蛋白质 - 蛋白质相互作用的广义方法

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摘要

Viral infection involves a large number of protein-protein interactions (PPIs) between virus and its host. These interactions range from the initial binding of viral coat proteins to host membrane receptor to the hijacking the host transcription machinery by viral proteins. Therefore, identifying PPIs between virus and its host helps understand the mechanism of viral infections and design antiviral drugs. Many computational methods have been developed to predict PPIs, but most of them are intended for PPIs within a species rather than PPIs across different species such as PPIs between virus and host. In this study, we developed a prediction model of virus-host PPIs, which is applicable to new viruses and hosts. We tested the prediction model on independent datasets of virus-host PPIs, which were not used in training the model. Despite a low sequence similarity between proteins in training datasets and target proteins in test datasets, the prediction model showed a high performance comparable to the best performance of other methods for single virus-host PPIs. Our method will be particularly useful to find PPIs between host and new viruses for which little information is available. The program and support data are available at http://bclab.inha.ac.kr/VirusHostPPI .
机译：病毒感染涉及病毒与其宿主之间的大量蛋白质 - 蛋白质相互作用（PPI）。这些相互作用范围从病毒涂层蛋白的初始结合到宿主膜受体通过病毒蛋白捕获宿主转录机器。因此，鉴定病毒与其宿主之间的PPI有助于了解病毒感染和设计抗病毒药物的机制。已经开发了许多计算方法来预测PPI，但大多数涉及在物种中的PPI，而不是在病毒和宿主之间的PPI等不同物种中的PPI。在这项研究中，我们开发了一种病毒宿主PPI的预测模型，适用于新病毒和主持人。我们测试了在病毒主机PPI的独立数据集上的预测模型，这些模型不用于培训模型。尽管训练数据集中的蛋白质和测试数据集中的目标蛋白质之间存在低序列相似性，但预测模型显示出与单一病毒-TOR PPI的其他方法的最佳性能相当的高性能。我们的方法在主机和新病毒之间找到PPI是特别有用的，这很少有信息。程序和支持数据可在http://bclab.inha.ac.kr/virushostppi提供。

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