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

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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.