Integrating sub-pathway analysis to identify candidate drugs for COVID-19

Background: A novel coronavirus 2019 (COVID-19) has spread throughout China and received world attention and caused an acute respiratory disease. We aimed to explore potential therapeutic drugs for COVID-19 via computational approaches. Material and methods: The RNA sequencing datasets of COVID-19 were downloaded by using the Gene Expression Omnibus (GEO). The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used for examining the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs. RStudio software SubpathwayMiner package was utilized to conduct pathway analysis on DEGs affected by drugs found in the Connectivity Map (CMap) and Search Tool for the Retrieval of Interacting Genes (STRING) database was utilized to construct Protein-protein interaction (PPI) networks of DEGs. COVID-19-related pathways were integrated to identify potential novel drugs for COVID-19. Results: The results revealed that 1613 DEGs were acquired from GEO. We obtained 26 significant pathways of COVID-19 utilizing KEGG pathway analysis. We determined MAPK signaling pathway and 47 CMap small-molecule drugs that affected this pathway. The PPI network analysis revealed that the NRAS, PAK1, RAP1A, and GNG12 are closely associated with an overlapping pathway (MAPK). Further literature verification results indicated that the effect of fluticasone and monensin on COVID-19 has been studied. Conclusions: Ambroxol, cefotiam, and benzathine benzylpenicillin have never been addressed for COVID-19 in the literature and they might be potential novel drugs for this disease. In-vitro, in-vivo and further studies are required to verify the molecular mechanism and definite effects of the novel potential drugs on COVID-19.