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

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

doi:10.1186/s12911-020-01373-x

Abstract

BackgroundThe 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.MethodsIn 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.ResultsWe 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.ConclusionsThe 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.

Highlights

The Coronavirus Disease 2019 (COVID-19) pandemic has infected over 10 million people globally with a relatively high mortality rate
By June 29, 2020, there were over 2,500,000 confirmed cases of Coronavirus Disease 2019 (COVID-19) in the U.S and over 10 million cases globally, based on the COVID-19 Dashboard [1] operated by the Center for Systems Science and Engineering at Johns Hopkins University (JHU)
We aimed to identify activated signaling pathways within lung host cells affected by SARS-CoV-2 and repurpose existing drugs for COVID-19 treatment using a novel integrative data analysis approach, integrating transcriptional response [14], signaling pathway [10], 15, gene ontology [16], drug-target interactions from drugbank [17] and reverse gene signature data from connectivity map (CMAP) [18,19,20]

Summary

Introduction

The Coronavirus Disease 2019 (COVID-19) pandemic has infected over 10 million people globally with a relatively high mortality rate. After affected by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCoV-2), molecular signaling pathways of host cells play critical roles during the life cycle of SARS-CoV-2. 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. By June 29, 2020, there were over 2,500,000 confirmed cases (with > 120,000 deaths) of Coronavirus Disease 2019 (COVID-19) in the U.S and over 10 million cases (with > 500,000 deaths) globally, based on the COVID-19 Dashboard [1] operated by the Center for Systems Science and Engineering at Johns Hopkins University (JHU). There is no newly FDA approved drug for the treatment of COVID-19. To improve the outcome of COVID-19 patients, many existing drugs are being

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