论文标题
使用概率网络和众包策划的药物重新利用COVID-19的预测
Drug repurposing prediction for COVID-19 using probabilistic networks and crowdsourced curation
论文作者
论文摘要
严重的急性呼吸综合症冠状病毒二（SARS-COV-2），该病毒是2019年冠状病毒病（COVID-19）大流行病，代表了前所未有的全球健康挑战。因此，对疾病发病机理和潜在治疗的大量研究是在短时间内进行的。但是，开发新型药物是一个昂贵且漫长的过程，不太可能为大流行提供及时的治疗。相比之下，药物重新利用提供了一种有吸引力的替代方法，因为现有药物已经经历了许多监管要求。在这项工作中，我们使用网络算法和人类策划的组合来搜索综合知识图，从而确定了COVID-19的药物重新利用机会。我们证明了这种方法的价值，报告了确定的八个潜在重新利用机会，并讨论如何将这种方法纳入未来的研究中。
Severe acute respiratory syndrome coronavirus two (SARS-CoV-2), the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic, represents an unprecedented global health challenge. Consequently, a large amount of research into the disease pathogenesis and potential treatments has been carried out in a short time frame. However, developing novel drugs is a costly and lengthy process, and is unlikely to deliver a timely treatment for the pandemic. Drug repurposing, by contrast, provides an attractive alternative, as existing drugs have already undergone many of the regulatory requirements. In this work we used a combination of network algorithms and human curation to search integrated knowledge graphs, identifying drug repurposing opportunities for COVID-19. We demonstrate the value of this approach, reporting on eight potential repurposing opportunities identified, and discuss how this approach could be incorporated into future studies.
