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KMID : 1039620210110040312
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Korean Journal of Family Practice
2021 Volume.11 No. 4 p.312 ~ p.321
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Recurrent Neural Network Based Drug Repurposing to Address SARS-CoV-2 (COVID-19), and the in vitro Antiviral Efficacy of Peroxisome Proliferator-Activated Receptors-Gamma Agonist
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Kim Nam-Hee
Dong Jae-June
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Abstract
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Background: Acute respiratory distress syndrome resulting from coronavirus (COVID-19) infection is triggered by cytokine storms, so activation ofinhibitory modulators of inflammatory pathways has become a new candidate modality for COVID-19 treatment. This study utilized artificialintelligence (A.I.) to search databases, and compiled a list of 50 drugs deemed plausible candidates for COVID-19 treatment. We then designed a cellbasedin vitro assay to evaluate the efficacy of PPAR-γ agonists against viral induced inflammation.
Methods: We applied RNN screening to Drugbank and CORD-19 databases, and selected as the top 50 drug candidates those compounds that havethe highest docking energy with the main protease produced by SARS-CoV-2 infected cells. We then designed an in vitro study includingchloroquine, lopinavir, and remdesivir treated cells as controls, and cells treated with two PPAR-γ agonists as experimental groups. SARS-CoV-2infected cells were administered a range of concentrations of each drug, and inhibition-normalized infection ratios were derived using animmunofluorescence method.
Results: The positive control groups’ SI’s were >1 (chloroquine SI=9.28, remdesivir SI=4.56, lopinavir SI=3.5), confirming their inhibitory effects againstSARS-CoV-2 infection. However, chloroquine and lopinavir displayed high cytotoxicity, and Remdesivir displayed low cytotoxicity. The two PPAR-γagonist SIs indicated that they possess no inhibitory effect against SARS-CoV-2 infection, but are clinically safe.
Conclusion: The PPAR-γ agonists did not reduce numbers of SARS-CoV-2 infected cells. Nevertheless, this study has significance in that we introducedthe use of A.I. for rapid new drug development during the COVID pandemic.
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KEYWORD
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COVID-19, Artificial Intelligence, Peroxisome Proliferator-Activated Receptors, in vitro
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