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Rechecking the Centrality-Lethality Rule in the Scope of Protein Subcellular Localization Interaction Networks

机译:重新检查蛋白质亚细胞定位相互作用网络范围内的中心性至死性规则

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摘要

Essential proteins are indispensable for living organisms to maintain life activities and play important roles in the studies of pathology, synthetic biology, and drug design. Therefore, besides experiment methods, many computational methods are proposed to identify essential proteins. Based on the centrality-lethality rule, various centrality methods are employed to predict essential proteins in a Protein-protein Interaction Network (PIN). However, neglecting the temporal and spatial features of protein-protein interactions, the centrality scores calculated by centrality methods are not effective enough for measuring the essentiality of proteins in a PIN. Moreover, many methods, which overfit with the features of essential proteins for one species, may perform poor for other species. In this paper, we demonstrate that the centrality-lethality rule also exists in Protein Subcellular Localization Interaction Networks (PSLINs). To do this, a method based on Localization Specificity for Essential protein Detection (LSED), was proposed, which can be combined with any centrality method for calculating the improved centrality scores by taking into consideration PSLINs in which proteins play their roles. In this study, LSED was combined with eight centrality methods separately to calculate Localization-specific Centrality Scores (LCSs) for proteins based on the PSLINs of four species (Saccharomyces cerevisiae, Homo sapiens, Mus musculus and Drosophila melanogaster). Compared to the proteins with high centrality scores measured from the global PINs, more proteins with high LCSs measured from PSLINs are essential. It indicates that proteins with high LCSs measured from PSLINs are more likely to be essential and the performance of centrality methods can be improved by LSED. Furthermore, LSED provides a wide applicable prediction model to identify essential proteins for different species.
机译:必需蛋白质对于生命有机体维持生命活动必不可少,并在病理学,合成生物学和药物设计研究中发挥重要作用。因此,除了实验方法外,还提出了许多计算方法来鉴定必需蛋白。基于中心性-致命性规则,采用各种中心性方法来预测蛋白质-蛋白质相互作用网络(PIN)中的必需蛋白质。然而,忽略蛋白质间相互作用的时间和空间特征,通过中心度方法计算的中心度得分不足以有效地测量PIN中蛋白质的本质。此外,许多方法过度适合一种物种的必需蛋白质的功能,但对其他物种可能效果不佳。在本文中,我们证明蛋白质亚细胞定位相互作用网络(PSLINs)中也存在中心致命性规则。为此,提出了一种基于基本蛋白质检测定位特异性(LSED)的方法,该方法可与任何中心方法相结合,通过考虑蛋白质在其中发挥作用的PSLIN来计算提高的中心评分。在这项研究中,LSED分别与八种中心方法相结合,基于四种物种(酿酒酵母,智人,小家鼠和果蝇果蝇)的PSLIN计算蛋白质的定位特异性中心值(LCS)。与通过全局PIN测量的具有较高中心评分的蛋白质相比,从PSLIN测量的具有更高LCS的蛋白质至关重要。这表明从PSLINs检测到的具有高LCS的蛋白质更可能是必不可少的,并且LSED可以改善中心法的性能。此外,LSED提供了广泛适用的预测模型,可识别不同物种的必需蛋白质。

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