Heterogeneous network-based drug repurposing for COVID-19

• URL: http://arxiv.org/abs/2107.09217v1
• Date: Tue, 20 Jul 2021 01:24:40 GMT
• Title: Heterogeneous network-based drug repurposing for COVID-19
• Authors: Shuting Jin, Xiangxiang Zeng, Wei Huang, Feng Xia, Changzhi Jiang, Xiangrong Liu and Shaoliang Peng
• Abstract summary: 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. 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.
• Score: 7.097880564431694
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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