Interactions between SARS-CoV-2 and human proteins (SARS-CoV-2 PPIs) cause information transfer through biochemical pathways that contribute to the immunopathology of COVID-19. Here, we present a communication network model of the immune system to compute the information transferred by the viral proteins using the available SARS-CoV-2 PPIs data. The amount of transferred information depends on the reference state of the immune system, or the state without SARS-CoV-2 PPIs, and can quantify how many variables of the immune system are controlled by the viral proteins. The information received by the immune system proteins from the viral proteins is useful to identify the biological processes (BPs) susceptible to dysregulation, and also to estimate the duration of viral PPIs necessary for the dysregulation to occur. We found that computing the drop in information from viral PPIs due to drugs provides a direct measure for the efficacy of therapies.
翻译:SARS-COV-2和人类蛋白质(SARS-COV-2 PPIs)之间的相互作用通过有助于COVID-19免疫病理学的生化途径进行信息传输。这里,我们展示了免疫系统的通信网络模型,以利用现有的SARS-COV-2 PPIs数据计算病毒蛋白质传播的信息。传输信息的数量取决于免疫系统的参考状态,或没有SARS-COV-2 PPPIs的国家,并可以量化免疫系统有多少变量受病毒蛋白的控制。免疫系统从病毒蛋白体获得的信息有助于确定易发生衰变的生物过程,并估计发生畸变所需的病毒PPPIs的持续时间。我们发现,计算病毒PPIs因药物而出现的信息下降,是治疗效果的直接措施。