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Improving prediction of heterodimeric protein complexes using combination with pairwise kernel

机译:与成对核结合改进对异二聚体蛋白复合物的预测

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摘要

BackgroundSince many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers.
机译:背景由于许多蛋白质只有在与其伴侣蛋白质相互作用并形成蛋白质复合物后才能发挥功能,因此鉴定形成复合物的蛋白质组至关重要。因此,已经提出了几种计算方法来从实验蛋白-蛋白相互作用(PPI)网络的拓扑和结构预测复合物。这些方法可以很好地预测涉及至少三种蛋白质的复合物,但是通常无法鉴定仅涉及两种不同蛋白质的复合物,称为异二聚体复合物或异二聚体。然而,迫切需要有效的方法来预测异二聚体,因为大多数已知的蛋白质复合物恰好是异二聚体。

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