A collaborative team of Canadian researchers used a database of over 10,000 drugs and an artificial intelligence system to find compounds that may be effective against coronaviruses, including SARS-CoV-2. The team included researchers at UHN, the University of Toronto, St. Michael’s Hospital and the Vector Institute for Artificial Intelligence.
As we have seen, viruses can quickly adapt and give rise to new variants. While developing treatments is key, it can take years for a new drug to be approved. That is why it is so important to find existing drugs that can be repurposed and quickly deployed.
“Identifying drugs strictly using their known functions, such as their ability to treat other viral diseases, is limiting. Instead, we expanded the search by developing a data-driven computational approach,” says Techna Scientist Dr. Bo Wang, who co-led the research team.
The strategy used by the team is called a “multiscale interactome approach”, where the relationships between diseases, proteins, biological pathways and other data are used to predict new interactions. Machine-learning tools are used to predict how drugs and the proteins that they target interact, and this information is used to identify useful interactions that may interrupt the infection process.
The researchers included 26 proteins from SARS-CoV-2, the virus behind the COVID-19 pandemic, in their models. The 26 virus proteins interact with 332 proteins in the human body. These human proteins represented a valuable resource in the search for antivirals. This is because drugs that are known to interact with them would be expected to affect the infection process.
Applying the artificial intelligence approach, the team identified 26 drugs that had the potential to treat Covid-19. They then tested several in single-cell experimental infections, and found that capmatinib, an anticancer drug, was able to neutralize the ability of SARS-CoV-2 to infect cells at doses that were likely safe for human use. The team then tested capmatinib against other coronaviruses and found that it had broad antiviral activity.
The study also identified a pair of related proteins—IRAK1 and IRAK4—as being necessary for SARS-CoV-2 to infect human cells. How viruses interact with these proteins is poorly understood, but they are present in bronchial cells, which are found in the airways. Furthermore, several of the drugs identified in the study worked by targeting IRAK1/IRAK4.
“Our method represents a new and powerful approach to rapidly identify new therapies using existing drugs. To our knowledge, our study is among the early attempts to demonstrate that this anticancer drug also has antiviral activity against coronaviruses—making it particularly promising as a therapy against SARS-CoV-2. Our screen also identified drugs that have already been shown to inhibit coronavirus infection, which validates our approach,” concludes Dr. Wang.
This work was supported by the Canadian Institute for Advanced Research, the Natural Sciences and Engineering Research Council of Canada, Mitacs, the EU Horizon 2020 program, the Government of Ontario, the Ryerson University Faculty of Science and the UHN Foundation. Dr. Roberto Botelho holds a Tier 2 Canada Research Chair in Biomedical Sciences and Technologies, Dr. Jean-Philippe Julien holds a Tier 2 Canada Research Chair in Structural Immunology. Dr. Bo Wang is an Assistant Professor in the Department of Medical Biophysics at the University of Toronto.
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 2;11(1):23315. doi: 10.1038/s41598-021-02432-7.