论文标题
SARS-COV-2/人类Interactome的网络分析和疾病子网
Network analysis and disease subnets for the SARS-CoV-2/Human interactome
论文作者
论文摘要
动机：为了在SARS-COV-2的情况下放大病毒人类蛋白质的相互作用并理解其相互作用，我们对蛋白质相互作用网络进行了结构性分析，从三个来源的整合中获得的蛋白质相互作用网络：1）病毒sars-cov-2，2）与人类蛋白质之间的蛋白质相互作用，这些蛋白质与人类蛋白质之间的相互作用，这些蛋白质与人类蛋白质之间的相互作用相互作用，这些蛋白质与人类蛋白质之间的相互作用相互作用，3）蛋白质相互作用，这些蛋白质的相互作用与这些蛋白质之间的相互作用，3）在3）中涉及这些相互作用，3）3）蛋白质与蛋白质有关。 结果：作为这项研究的产物，我们提出了两个网络，一个网络来自相互作用病毒宿主，另一个限于宿主主持人，通常不考虑最后一个网络进行网络分析。 We identified the most important proteins in both networks, those that have the maximal value of calculated invariants, these proteins are considered as the most: affected, connected or those that best monitor the flow of information in the network, among them we find UBC, a human protein related with ubiquination, linked with different stages of coronavirus disease, and ORF7A a virus protein that induces apoptosis in infected cells, associated with virion绑扎。使用构造的网络，我们建立了与人蛋白及其与其他蛋白质的联系相对应的更重要的疾病。相关的是，所鉴定的疾病与合并症一致，尤其是糖尿病的子网涉及大量病毒和人类蛋白质（56％）和相互作用（60％），这可以解释这种状况作为疾病并发症的重要原因。
Motivation: With the aim to amplify and make sense of interactions of virus-human proteins in the case of SARS-CoV-2, we performed a structural analysis of the network of protein interactions obtained from the integration of three sources: 1) proteins of virus SARS-CoV-2, 2)physical interactions between SARS-CoV-2 and human proteins, 3) known interactions of these human proteins between them and the dossier of affections in which these proteins are implicated. Results: As a product of this research, we present two networks, one from the interactions virus-host, and the other restricted to host-host, the last one is not usually considered for network analysis. We identified the most important proteins in both networks, those that have the maximal value of calculated invariants, these proteins are considered as the most: affected, connected or those that best monitor the flow of information in the network, among them we find UBC, a human protein related with ubiquination, linked with different stages of coronavirus disease, and ORF7A a virus protein that induces apoptosis in infected cells, associated with virion tethering. Using the constructed networks, we establish the more significant diseases corresponding with human proteins and their connections with other proteins. It is relevant that the identified diseases coincide with comorbidities, particularly the subnetwork of diabetes involves a great quantity of virus and human proteins (56%) and interactions (60%), this could explain the effect of this condition as an important cause of disease complications.
