The Corona Virus Disease 2019 (COVID-19) belongs to human coronaviruses (HCoVs), which spreads rapidly around the world. Compared with new drug development, drug repurposing may be the best shortcut for treating COVID-19. Therefore, we constructed a comprehensive heterogeneous network based on the HCoVs-related target proteins and use the previously proposed deepDTnet, to discover potential drug candidates for COVID-19. We obtain high performance in predicting the possible drugs effective for COVID-19 related proteins. In summary, this work utilizes a powerful heterogeneous network-based deep learning method, which may be beneficial to quickly identify candidate repurposable drugs toward future clinical trials for COVID-19. The code and data are available at https://github.com/stjin-XMU/HnDR-COVID.
翻译:2019年科罗纳病毒疾病(COVID-19)属于迅速蔓延到世界各地的人类冠状病毒(HCOVs),与新的药物开发相比,药物重新定位可能是治疗COVID-19的最佳捷径,因此,我们根据与HCOVs有关的目标蛋白并使用先前提议的深DTnet,建立了一个综合的多元网络,以发现COVID-19的潜在药物候选者。我们在预测对COVID-19有关蛋白可能有效的药物方面取得很高的成绩。 总之,这项工作采用了一种强大的基于网络的多样化的深层次学习方法,这可能有助于迅速确定可用于COVID-19今后临床试验的候选药物。代码和数据见https://gitub.comstjin-XMU/HnDR-COVID。