The COVID-19 pandemic has claimed millions of lives worldwide and could continue to pose problems in the future. In fact, a number of epidemiological models have shown that the virus may very well become endemic. The challenges associated with the development of therapies against infections with the SARS-CoV-2 virus are compounded by the sporadic apparition of novel variants and strains. SARS-CoV-2 virus depends on the interaction between its Spike protein and the human Angiotensin-Converting Enzyme 2 (hACE2) protein to enter the cells. Once in the cell, viral proteins are involved in a variety of processesthat trigger inflammation and an exaggerated immune response –the so-called “cytokine storm”. Preliminary work completed by our lab has allowed us to identify a high-quality prediction of the comprehensive inter-species interactome, and to identify relevant biological pathways that contribute to the pathological phenotype of the COVID-19 disease. Our current work aims to design short peptides that can effectively disrupt relevant interactions we previously identified between SARS-CoV-2 proteins and human proteins. To this end, we will develop evolutionary algorithmsthat leverage bothin silico protein-protein interaction predictors and in vitropeptidearrays in an iterativeway. Not only will the methodology developed in this work be applicable for the development of therapeutics against COVID-19 and its variants, it will also provide a systematic pipeline that can be deployed for the design anti-viral peptides more broadly.Such a pipeline will be critical to rapidly address future pandemics.

Industry Partner(s):NuvoBio Corporation

Academic Institution:Carleton University

Academic Researcher: Green, James R.

Focus Areas: COVID-19, Health

Platforms: GPU, Parallel CPU