Heterogeneous network-based drug repurposing for COVID-19

2021/07/20 by Shuting Jin, Jin, Shuting, Xiangxiang Zeng +11
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · #Cell Image Analysis Techniques #Computational Drug Discovery Methods #Computers and Society (cs.CY) #FOS: Computer and information sciences #Innovative Microfluidic and Catalytic Techniques Innovation #Machine Learning (cs.LG)

paper · pdf · doi:10.48550/arxiv.2107.09217

openalex publication_date 2021/07/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

Citations

• Coronavirus Infections—More Than Just the Common Cold
• Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

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