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Computational prediction of protein-protein interactions in sphingolipid signaling network

机译:鞘脂信号网络中蛋白质相互作用的计算预测

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Proteins carry out most of the work in the cell such as immunological recognition, DNA repair and replication, enzymatic activity, cell signaling by interacting with other proteins. Therefore, elucidation of the protein-protein interaction network will assist in understanding molecular mechanism of cellular activities. Recent advances in high-throughput experimental methods have provided a large amount of data that need to be sorted and interpreted to find biologically relevant interactions and pathways. In silico methods that can accurately predict properties of protein-protein interactions have gained increased interest. In this study, the network of sphingolipid (SL) signaling proteins was constructed using computational prediction methods to contribute to missing interactions among the components of sphingolipid protein-protein interaction (PPI) network. As a result of the studies by our group, the potential protein interactions between YER019W-YHL020C and YGR143W-YKL126W were identified. The new predictions proposed by this research can guide rational design of new experiments.
机译:蛋白质通过与其他蛋白质相互作用,在细胞中执行大部分工作,例如免疫识别,DNA修复和复制,酶活性,细胞信号传导。因此,阐明蛋白质间相互作用网络将有助于理解细胞活性的分子机制。高通量实验方法的最新进展提供了大量数据,需要对其进行分类和解释以找到生物学上相关的相互作用和途径。可以精确预测蛋白质-蛋白质相互作用特性的计算机方法已引起越来越多的关注。在这项研究中,鞘脂(SL)信号蛋白的网络是使用计算预测方法构建的,以有助于鞘脂蛋白-蛋白相互作用(PPI)网络的组件之间缺少相互作用。根据我们小组的研究结果,确定了YER019W-YHL020C和YGR143W-YKL126W之间潜在的蛋白质相互作用。这项研究提出的新预测可以指导新实验的合理设计。

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