School of Life Sciences, Shanghai University, Shanghai 200444, China.
Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
Biomed Res Int. 2020 Jul 8;2020:4256301. doi: 10.1155/2020/4256301. eCollection 2020.
Coronaviruses are specific crown-shaped viruses that were first identified in the 1960s, and three typical examples of the most recent coronavirus disease outbreaks include severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19. Particularly, COVID-19 is currently causing a worldwide pandemic, threatening the health of human beings globally. The identification of viral pathogenic mechanisms is important for further developing effective drugs and targeted clinical treatment methods. The delayed revelation of viral infectious mechanisms is currently one of the technical obstacles in the prevention and treatment of infectious diseases. In this study, we proposed a random walk model to identify the potential pathological mechanisms of COVID-19 on a virus-human protein interaction network, and we effectively identified a group of proteins that have already been determined to be potentially important for COVID-19 infection and for similar SARS infections, which help further developing drugs and targeted therapeutic methods against COVID-19. Moreover, we constructed a standard computational workflow for predicting the pathological biomarkers and related pharmacological targets of infectious diseases.
冠状病毒是特定的冠状病毒，于 20 世纪 60 年代首次被发现，最近爆发的三种典型冠状病毒疾病包括严重急性呼吸系统综合征（SARS）、中东呼吸系统综合征（MERS）和 COVID-19。特别是，COVID-19 目前正在导致全球大流行，威胁着全球人类的健康。鉴定病毒的发病机制对于进一步开发有效的药物和靶向临床治疗方法很重要。病毒感染机制的揭示延迟是目前传染病预防和治疗的技术障碍之一。在这项研究中，我们提出了一个随机游走模型，用于鉴定病毒-人类蛋白质相互作用网络中 COVID-19 的潜在病理机制，我们有效地鉴定了一组已经被确定为 COVID-19 感染和类似 SARS 感染的潜在重要蛋白，这有助于进一步开发针对 COVID-19 的药物和靶向治疗方法。此外，我们构建了一个标准的计算工作流程，用于预测传染病的病理生物标志物和相关的药理靶点。
