Integrating druggability and genetic variability of coronavirus genomes to inform drug discovery against COVID‑19 and future pandemic threats

Schapira, Matthieu | $50,000

Ontario University of Toronto 2020 NSERC Alliance COVID-19 Grant

In partnership and after consultation with Cyclica, a Canadian biotech, we propose to use computer modelling to integrate genetic and structural data on the SARS-CoV-2 genome available from international public repositories. Using advanced structural bioinformatic tools, we will map genetic mutations from thousands of SARS-CoV-2 variants onto crystal structures of SARS-CoV-2 proteins to identify binding sites most amenable for the development of broad-spectrum inhibitors. We will then extend this exercise to coronavirus strains beyond SARS-CoV-2 to identify opportunities for the development of pan-coronavirus inhibitors. We will share all the knowledge generated on a Canadian online portal, which will become a valuable resource for drug discovery efforts at Cyclica, in Canada and around the world focused on the COVID‑19 crisis. While the proposed work is a computational analysis of the COVID‑19 and other coronavirus genomes, and is therefore not applied research, the knowledge generated will inform COVID‑19 drug discovery efforts ongoing by our Alliance partner.

With funding from the Government of Canada

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