Protein–protein interaction networks have been used to investigate the influence of SARS-CoV-2 viral proteins on the function of human cells, laying out a deeper understanding of COVID–19 and providing ground for applications, such as drug repurposing. Characterizing molecular (dis)similarities between SARS-CoV-2 and other viral agents allows one to exploit existing information about the alteration of key biological processes due to known viruses for predicting the potential effects of this new virus. Here, we compare the novel coronavirus network against 92 known viruses, from the perspective of statistical physics and computational biology. We show that regulatory spreading patterns, physical features and enriched biological pathways in targeted proteins lead, overall, to meaningful clusters of viruses which, across scales, provide complementary perspectives to better characterize SARS-CoV-2 and its effects on humans. Our results indicate that the virus responsible for COVID–19 exhibits expected similarities, such as to Influenza A and Human Respiratory Syncytial viruses, and unexpected ones with different infection types and from distant viral families, like HIV1 and Human Herpes virus. Taken together, our findings indicate that COVID–19 is a systemic disease with potential effects on the function of multiple organs and human body sub-systems.

蛋白质-蛋白质相互作用网络已被用于研究SARS-CoV-2病毒蛋白对人类细胞功能的影响，对COVID-19有了更深的了解，并为诸如药物再利用等应用提供了基础。表征SARS-CoV-2与其他病毒制剂之间的分子（异）相似性，使人们能够利用有关已知病毒引起的关键生物学过程改变的现有信息来预测这种新病毒的潜在作用。在这里，我们从统计物理学和计算生物学的角度比较了新型冠状病毒网络与92种已知病毒。我们表明，靶向蛋白中的调控扩散模式，物理特征和丰富的生物途径总体上导致了有意义的病毒簇，这些病毒跨规模，提供互补的观点，以更好地表征SARS-CoV-2及其对人类的影响。我们的结果表明，负责COVID-19的病毒表现出预期的相似性，例如与甲型流感和人类呼吸道合胞病毒以及具有不同感染类型且来自遥远病毒家族的意想不到的相似性，如HIV1和人类疱疹病毒。综上所述，我们的发现表明COVID-19是一种系统性疾病，对多个器官和人体子系统的功能具有潜在影响。例如HIV1和人类疱疹病毒。综上所述，我们的发现表明COVID-19是一种系统性疾病，对多个器官和人体子系统的功能具有潜在影响。例如HIV1和人类疱疹病毒。综上所述，我们的发现表明COVID-19是一种系统性疾病，对多个器官和人体子系统的功能具有潜在影响。