论文标题
免疫系统的通信网络模型确定与SARS-COV-2蛋白相互作用的影响
Communication network model of the immune system identifies the impact of interactions with SARS-CoV-2 proteins
论文作者
论文摘要
SARS-COV-2与人类蛋白（SARS-COV-2 PPI）之间的相互作用通过生化途径导致信息传递，从而导致COVID-19的免疫病理学。在这里，我们提出了一种免疫系统的通信网络模型，以使用可用的SARS-COV-2 PPIS数据来计算病毒蛋白传输的信息。传递的信息的量取决于免疫系统的参考状态，或没有SARS-COV-2 PPI的状态，并且可以量化免疫系统的多少变量由病毒蛋白控制。免疫系统蛋白从病毒蛋白收到的信息对于识别易于失调的生物学过程（BPS）很有用，也可以估计发生失调所必需的病毒PPI持续时间。我们发现，计算因药物而导致的病毒PPI的信息下降提供了一种直接衡量疗法功效的方法。
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.
