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Author Notes:

Jeffrey Skolnick, Email: skolnick@gatech.edu

C.A., H.Z. and J.S. conceived of LeMeDISCO; H.Z. and J.S. developed LeMeDISCO and CoMOAdrug; H.Z. developed CoVLS; J.S. conceived of the idea of applying LeMeDISCO to SARS-CoV-2; C.A., J.J., H.Z., and J.S. analyzed the data and wrote the paper.

We thank Bartosz Ilkowski for internal computing support, Jessica Forness for proof-reading the manuscript and Hongnan Conan for bringing the GWAS study to the authors’ attention and Mu Gao for insightful discussions.

The authors declare no competing interests.


Research Funding:

This project was funded by R35 GM-118039 of the Division of General Medical Sciences of the NIH.


  • Science & Technology
  • Multidisciplinary Sciences
  • Science & Technology - Other Topics

Prediction of severe adverse events, modes of action and drug treatments for COVID-19's complications


Journal Title:



Volume 11, Number 1


, Pages 20864-20864

Type of Work:

Article | Final Publisher PDF


Following SARS-CoV-2 infection, some COVID-19 patients experience severe host driven adverse events. To treat these complications, their underlying etiology and drug treatments must be identified. Thus, a novel AI methodology MOATAI-VIR, which predicts disease-protein-pathway relationships and repurposed FDA-approved drugs to treat COVID-19’s clinical manifestations was developed. SARS-CoV-2 interacting human proteins and GWAS identified respiratory failure genes provide the input from which the mode-of-action (MOA) proteins/pathways of the resulting disease comorbidities are predicted. These comorbidities are then mapped to their clinical manifestations. To assess each manifestation’s molecular basis, their prioritized shared proteins were subject to global pathway analysis. Next, the molecular features associated with hallmark COVID-19 phenotypes, e.g. unusual neurological symptoms, cytokine storms, and blood clots were explored. In practice, 24/26 of the major clinical manifestations are successfully predicted. Three major uncharacterized manifestation categories including neoplasms are also found. The prevalence of neoplasms suggests that SARS-CoV-2 might be an oncovirus due to shared molecular mechanisms between oncogenesis and viral replication. Then, repurposed FDA-approved drugs that might treat COVID-19’s clinical manifestations are predicted by virtual ligand screening of the most frequent comorbid protein targets. These drugs might help treat both COVID-19’s severe adverse events and lesser ones such as loss of taste/smell.

Copyright information:

© The Author(s) 2021

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/rdf).
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