论文标题
重新定位8565种现有药物用于COVID-19
Repositioning of 8565 existing drugs for COVID-19
论文作者
论文摘要
严重急性呼吸综合症2（SARS-COV-2）引起的冠状病毒疾病2019年（Covid-19）大流行已感染了近500万人，并导致超过30万人死亡。目前，没有特定的抗SARS-COV-2药物。新药发现通常需要十多年。药物重新定位成为对抗COVID-19的最可行的方法之一。这项工作策划了SARS-COV-2或SARS-COV主要蛋白酶抑制剂的最大可用实验数据集。基于此数据集，我们开发了具有相对较低根平方误差的经过验证的机器学习模型，以屏幕1553 FDA批准的药物以及其他7012个药物库中的7012个研究或外市场药物。我们发现，许多现有药物可能对SARS-COV-2有效。分析了许多有效的SARS-COV-2主要蛋白酶抑制剂的吸毒性。这项工作为COVID-19药物重新定位的进一步实验研究奠定了基础。
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected near 5 million people and led to over 0.3 million deaths. Currently, there is no specific anti-SARS-CoV-2 medication. New drug discovery typically takes more than ten years. Drug repositioning becomes one of the most feasible approaches for combating COVID-19. This work curates the largest available experimental dataset for SARS-CoV-2 or SARS-CoV main protease inhibitors. Based on this dataset, we develop validated machine learning models with relatively low root mean square error to screen 1553 FDA-approved drugs as well as other 7012 investigational or off-market drugs in DrugBank. We found that many existing drugs might be potentially potent to SARS-CoV-2. The druggability of many potent SARS-CoV-2 main protease inhibitors is analyzed. This work offers a foundation for further experimental studies of COVID-19 drug repositioning.
