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Screening for clusters of charge in human virus proteomes

机译:筛选人类病毒蛋白质组中的电荷簇

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Background The identification of charge clusters (runs of charged residues) in proteins and their mapping within the protein structure sequence is an important step toward a comprehensive analysis of how these particular motifs mediate, via electrostatic interactions, various molecular processes such as protein sorting, translocation, docking, orientation and binding to DNA and to other proteins. Few algorithms that specifically identify these charge clusters have been designed and described in the literature. In this study, 197 distinctive human viral proteomes were screened for the occurrence of charge clusters (CC) using a new computational approach. Results Three hundred and seventy three CC have been identified within the 2549 viral protein sequences screened. The number of protein sequences that are CC-free is 2176 (85.3?%) while 150 and 180 proteins contained positive charge (PCC) and negative charge clusters (NCC), respectively. The NCCs (211 detected) were more prevalent than PCC (162). PCC-containing proteins are significantly longer than those having NCCs ( p =?2.10-16). The most prevalent virus families having PCC and NCC were Herpesviridae followed by Papillomaviridae . However, the single-strand RNA group has in average three times more NCC than PCC. According to the functional domain classification, a significant difference in distribution was observed between PCC and NCC ( p =?2. 10?8) with the occurrence of NCCs being more frequent in C-terminal region while PCC more often fall within functional domains. Only 29 proteins sequences contained both NCC and PCC. Moreover, 101 NCC were conserved in 84 proteins while only 62 PCC were conserved in 60 protein sequences. To understand the mechanism by which the membrane translocation functionalities are embedded in viral proteins, we screened our PCC for sequences corresponding to cell-penetrating peptides (CPPs) using two online databases: CellPPd and CPPpred . We found that all our PCCs, having length varying from 7 to 30 amino-acids were predicted as CPPs. Experimental validation is required to improve our understanding of the role of these PCCs in viral infection process. Conclusions Screening distinctive cluster charges in viral proteomes suggested a functional role of these protein regions and might provide potential clues to improve the current understanding of viral diseases in order to tailor better preventive and therapeutic approaches.
机译:背景鉴定蛋白质中的电荷簇(带电残基的序列)及其在蛋白质结构序列中的定位,是全面分析这些特定基序如何通过静电相互作用介导各种分子过程(如蛋白质分选,转运)的重要一步。 ,对接,定向以及与DNA和其他蛋白质的结合。文献中很少设计和描述专门识别这些电荷簇的算法。在这项研究中,使用一种新的计算方法筛选了197种独特的人类病毒蛋白质组是否存在电荷簇(CC)。结果在筛选的2549个病毒蛋白序列中鉴定出了373个CC。不含CC的蛋白质序列数量为2176(85.3%),而150和180的蛋白质分别包含正电荷(PCC)和负电荷簇(NCC)。 NCC(检测到211个)比PCC(162个)更普遍。含有PCC的蛋白质明显长于具有NCC的蛋白质(p =?2.10 -16 )。具有PCC和NCC的最流行的病毒家族是疱疹病毒科,其次是pil蝶科。但是,单链RNA组的NCC平均比PCC多三倍。根据功能域分类,在PCC和NCC之间观察到分布的显着差异(p =?2。10 ?8 ),其中NCC在C端区域的发生更为频繁,而PCC通常属于功能范围。只有29个蛋白质序列同时包含NCC和PCC。此外,101个NCC在84个蛋白质中保守,而在62个PCC中60个蛋白质序列中保守。为了了解膜易位功能嵌入病毒蛋白的机制,我们使用两个在线数据库CellPPd和CPPpred筛选了PCC中与细胞穿透肽(CPPs)相对应的序列。我们发现,长度在7至30个氨基酸之间的所有PCC均被预测为CPP。需要进行实验验证来增进我们对这些PCC在病毒感染过程中的作用的了解。结论筛选病毒蛋白质组中独特的簇电荷表明这些蛋白质区域的功能性作用,并可能提供潜在线索,以改善当前对病毒性疾病的了解,从而制定更好的预防和治疗方法。

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