Prediction of potential therapeutic drugs against SARS-CoV-2 by using Connectivity Map based on transcriptome data

Area of Science:

• Genomics
• Virology
• Immunology

Background:

• Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) is a novel virus causing significant global health concerns.
• Understanding the molecular impact of SARS-CoV-2 on human cells is crucial for developing effective treatments.

Purpose of the Study:

• To analyze the influence of SARS-CoV-2 on human cellular transcriptomes.
• To identify potential therapeutic compounds against SARS-CoV-2 by screening known drugs.

Main Methods:

• Differential gene expression analysis using DESeq2 on SARS-CoV-2 infected and non-infected cells.
• Gene Ontology (GO) and KEGG pathway enrichment analysis of differentially expressed genes (DEGs).
• Construction of a protein-protein interaction (PPI) network and screening of compounds using the Connectivity Map (CMap) database.

Main Results:

• A total of 145 DEGs were identified, with 136 upregulated and 9 downregulated in infected cells.
• Enrichment analyses highlighted pathways related to viral infection, inflammation, and immunity.
• Triptolide, tivozanib, and daunorubicin were identified as potential therapeutic compounds with significant reverse genomic effects.

Conclusions:

• SARS-CoV-2 induces widespread molecular and signaling pathway alterations in human cells.
• IL-17 and TNF signaling pathways may be critical in SARS-CoV-2 pathogenesis.
• The identified compounds offer potential new therapeutic strategies for SARS-CoV-2 treatment.