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Published in: BMC Medical Informatics and Decision Making 1/2021

Open Access 01-12-2021 | SARS-CoV-2 | Research article

Computational analysis to repurpose drugs for COVID-19 based on transcriptional response of host cells to SARS-CoV-2

Authors: Fuhai Li, Andrew P. Michelson, Randi Foraker, Ming Zhan, Philip R. O. Payne

Published in: BMC Medical Informatics and Decision Making | Issue 1/2021

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Abstract

Background

The Coronavirus Disease 2019 (COVID-19) pandemic has infected over 10 million people globally with a relatively high mortality rate. There are many therapeutics undergoing clinical trials, but there is no effective vaccine or therapy for treatment thus far. After affected by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), molecular signaling pathways of host cells play critical roles during the life cycle of SARS-CoV-2. Thus, it is significant to identify the involved molecular signaling pathways within the host cells. Drugs targeting these molecular signaling pathways could be potentially effective for COVID-19 treatment.

Methods

In this study, we developed a novel integrative analysis approach to identify the related molecular signaling pathways within host cells, and repurposed drugs as potentially effective treatments for COVID-19, based on the transcriptional response of host cells.

Results

We identified activated signaling pathways associated with the infection caused SARS-CoV-2 in human lung epithelial cells through integrative analysis. Then, the activated gene ontologies (GOs) and super GOs were identified. Signaling pathways and GOs such as MAPK, JNK, STAT, ERK, JAK-STAT, IRF7-NFkB signaling, and MYD88/CXCR6 immune signaling were particularly activated. Based on the identified signaling pathways and GOs, a set of potentially effective drugs were repurposed by integrating the drug-target and reverse gene expression data resources. In addition to many drugs being evaluated in clinical trials, the dexamethasone was top-ranked in the prediction, which was the first reported drug to be able to significantly reduce the death rate of COVID-19 patients receiving respiratory support.

Conclusions

The integrative genomics data analysis and results can be helpful to understand the associated molecular signaling pathways within host cells, and facilitate the discovery of effective drugs for COVID-19 treatment.
Appendix
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Metadata
Title
Computational analysis to repurpose drugs for COVID-19 based on transcriptional response of host cells to SARS-CoV-2
Authors
Fuhai Li
Andrew P. Michelson
Randi Foraker
Ming Zhan
Philip R. O. Payne
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2021
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-020-01373-x

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