Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing

Naomi I. Maria; Rosaria Valentina Rapicavoli; Salvatore Alaimo; Evelyne Bischof; Alessia Stasuzzo; Jantine A.C. Broek; Alfredo Pulvirenti; Bud Mishra; Ashley J. Duits; Alfredo Ferro

Heliyon (Mar 2023)

Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing

Naomi I. Maria,
Rosaria Valentina Rapicavoli,
Salvatore Alaimo,
Evelyne Bischof,
Alessia Stasuzzo,
Jantine A.C. Broek,
Alfredo Pulvirenti,
Bud Mishra,
Ashley J. Duits,
Alfredo Ferro

Affiliations

Naomi I. Maria: Department of Computer Science, Mathematics, Engineering and Cell Biology, Courant Institute, Tandon and School of Medicine, New York University, New York, USA; Institute of Molecular Medicine, The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA; Department of Medicine, Donald and Barbara Zucker School of Medicine at Hofstra, Northwell Health, Manhasset, NY, USA; Red Cross Blood Bank Foundation Curaçao, Willemstad, Curaçao; Department of Medical Microbiology and Immunology, St. Antonius Ziekenhuis, Niewegein, the Netherlands; Corresponding author. Department of Computer Science, Mathematics, Engineering and Cell Biology, Courant Institute, Tandon and School of Medicine, New York University, New York, USA.
Rosaria Valentina Rapicavoli: Department of Physics and Astronomy, University of Catania, Italy; Bioinformatics Unit, Department of Clinical and Experimental Medicine, University of Catania, Italy
Salvatore Alaimo: Bioinformatics Unit, Department of Clinical and Experimental Medicine, University of Catania, Italy
Evelyne Bischof: Department of Advanced Biomedical Sciences, University of Naples Federico II, Via Pansini, Naples, Italy; School of Clinical Medicine, Shanghai University of Medicine and Health Sciences, Pudong, Shanghai, China; Insilico Medicine, Hong Kong Special Administrative Region, China
Alessia Stasuzzo: Department of Chemical Sciences, University of Catania, Italy
Jantine A.C. Broek: Department of Computer Science, Mathematics, Engineering and Cell Biology, Courant Institute, Tandon and School of Medicine, New York University, New York, USA
Alfredo Pulvirenti: Bioinformatics Unit, Department of Clinical and Experimental Medicine, University of Catania, Italy
Bud Mishra: Department of Computer Science, Mathematics, Engineering and Cell Biology, Courant Institute, Tandon and School of Medicine, New York University, New York, USA; Simon Center for Quantitative Biology, Cold Spring Harbor Lab, Long Island, USA; Corresponding author. Courant Institute of Mathematical Sciences, Room 405, 251 Mercer Street, NY, USA.
Ashley J. Duits: Red Cross Blood Bank Foundation Curaçao, Willemstad, Curaçao; Curaçao Biomedical Health Research Institute, Willemstad, Curaçao; Institute for Medical Education, University Medical Center Groningen, Groningen, the Netherlands
Alfredo Ferro: Bioinformatics Unit, Department of Clinical and Experimental Medicine, University of Catania, Italy

Journal volume & issue: Vol. 9, no. 3
p. e14115

Abstract

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The current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which -by leveraging available transcriptomic and proteomic databases-allows modeling of SARS-CoV-2 infection in host cells in silico to i) determine with high sensitivity and specificity (both>96%) the viral effects on cellular host-immune response, resulting in specific cellular SARS-CoV-2 signatures and ii) utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis.

Published in Heliyon

ISSN: 2405-8440 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Science (General); Social Sciences: Social sciences (General)
Website: https://www.cell.com/heliyon/home

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