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Sugiyama MG, Cui H, Redka DS, et al. Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease. Sci Rep. 2021;11(1):23315doi: 10.1038/s41598-021-02432-7.
Sugiyama, M. G., Cui, H., Redka, D. S., Karimzadeh, M., Rujas, E., Maan, H., Hayat, S., Cheung, K., Misra, R., McPhee, J. B., Viirre, R. D., Haller, A., Botelho, R. J., Karshafian, R., Sabatinos, S. A., Fairn, G. D., Madani Tonekaboni, S. A., Windemuth, A., Julien, J. P., Shahani, V., MacKinnon, S. S., Wang, B., & Antonescu, C. N. (2021). Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease. Scientific reports, 11(1), 23315. https://doi.org/10.1038/s41598-021-02432-7
Sugiyama, Michael G, et al. "Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease." Scientific reports vol. 11,1 (2021): 23315. doi: https://doi.org/10.1038/s41598-021-02432-7
Sugiyama MG, Cui H, Redka DS, Karimzadeh M, Rujas E, Maan H, Hayat S, Cheung K, Misra R, McPhee JB, Viirre RD, Haller A, Botelho RJ, Karshafian R, Sabatinos SA, Fairn GD, Madani Tonekaboni SA, Windemuth A, Julien JP, Shahani V, MacKinnon SS, Wang B, Antonescu CN. Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease. Sci Rep. 2021 Dec 02;11(1):23315. doi: 10.1038/s41598-021-02432-7. PMID: 34857794; PMCID: PMC8640055.
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Sci Rep. 2021 Dec 02;11(1):23315. doi: 10.1038/s41598-021-02432-7.

Multiscale interactome analysis coupled with off-target drug predictions reveals drug repurposing candidates for human coronavirus disease.

Scientific reports

Michael G Sugiyama, Haotian Cui, Dar'ya S Redka, Mehran Karimzadeh, Edurne Rujas, Hassaan Maan, Sikander Hayat, Kyle Cheung, Rahul Misra, Joseph B McPhee, Russell D Viirre, Andrew Haller, Roberto J Botelho, Raffi Karshafian, Sarah A Sabatinos, Gregory D Fairn, Seyed Ali Madani Tonekaboni, Andreas Windemuth, Jean-Philippe Julien, Vijay Shahani, Stephen S MacKinnon, Bo Wang, Costin N Antonescu

Affiliations

  1. Department of Chemistry and Biology, Ryerson University, Toronto, ON, Canada.
  2. Department of Computer Science, University of Toronto, Toronto, ON, Canada.
  3. Vector Institute, Toronto, ON, Canada.
  4. Cyclica Inc., Toronto, ON, Canada.
  5. Program in Molecular Medicine, The Hospital for Sick Children Research Institute, Toronto, ON, Canada.
  6. Department of Biochemistry, University of Toronto, Toronto, ON, Canada.
  7. Biofisika Institute (CSIC, UPV/EHU) and Department of Biochemistry and Molecular Biology, University of the Basque Country (UPV/EHU), Bilbao, Spain.
  8. Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
  9. Peter Munk Cardiac Centre, University Health Centre, Toronto, ON, Canada.
  10. Precision Cardiology Laboratory, Bayer US LLC, Cambridge, MA, USA.
  11. Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany.
  12. Graduate Program in Molecular Science, Ryerson University, Toronto, ON, Canada.
  13. Phoenox Pharma, Toronto, ON, Canada.
  14. Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, Canada.
  15. Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada.
  16. Institute for Biomedical Engineering, Science and Technology (iBEST), a partnership between Ryerson University and St. Michael's Hospital, Toronto, ON, Canada.
  17. Department of Physics, Ryerson University, Toronto, ON, Canada.
  18. Department of Surgery, University of Toronto, Toronto, ON, Canada.
  19. Department of Immunology, Toronto, ON, Canada.
  20. Cyclica Inc., Toronto, ON, Canada. [email protected].
  21. Department of Computer Science, University of Toronto, Toronto, ON, Canada. [email protected].
  22. Vector Institute, Toronto, ON, Canada. [email protected].
  23. Peter Munk Cardiac Centre, University Health Centre, Toronto, ON, Canada. [email protected].
  24. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada. [email protected].
  25. Department of Chemistry and Biology, Ryerson University, Toronto, ON, Canada. [email protected].
  26. Graduate Program in Molecular Science, Ryerson University, Toronto, ON, Canada. [email protected].
  27. Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada. [email protected].

PMID: 34857794 PMCID: PMC8640055 DOI: 10.1038/s41598-021-02432-7

Abstract

The COVID-19 pandemic has highlighted the urgent need for the identification of new antiviral drug therapies for a variety of diseases. COVID-19 is caused by infection with the human coronavirus SARS-CoV-2, while other related human coronaviruses cause diseases ranging from severe respiratory infections to the common cold. We developed a computational approach to identify new antiviral drug targets and repurpose clinically-relevant drug compounds for the treatment of a range of human coronavirus diseases. Our approach is based on graph convolutional networks (GCN) and involves multiscale host-virus interactome analysis coupled to off-target drug predictions. Cell-based experimental assessment reveals several clinically-relevant drug repurposing candidates predicted by the in silico analyses to have antiviral activity against human coronavirus infection. In particular, we identify the MET inhibitor capmatinib as having potent and broad antiviral activity against several coronaviruses in a MET-independent manner, as well as novel roles for host cell proteins such as IRAK1/4 in supporting human coronavirus infection, which can inform further drug discovery studies.

© 2021. The Author(s).

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