A bioinformatics method for identification of human proteases active against viral envelope glycoproteins: a case study on the SARS-CoV-2 spike protein

Abstract

Many viruses, including SARS-CoV-2, the coronavirus responsible for the COVID-19 pandemic, enter host cells through a process cell-viral membrane fusion that is activated by proteolytic enzymes. Typically, these enzymes are host cell proteases. Identifying the proteases that activate the virus is not a simple task but is important for the development of new antiviral drugs. In this study, we developed a bioinformatics method for identifying proteases that can cleave viral envelope glycoproteins. The proposed approach involves the use of predictive models for the substrate specificity of human proteases and the application of structural analysis method for predicting the vulnerability of protein regions to proteolysis based on their 3D structures. Specificity models were constructed for 169 human proteases using information on their known substrates. A previously developed method for structural analysis of potential proteolysis sites was applied in parallel with specificity models. Validation of the proposed approach was performed on the SARS-CoV-2 spike protein, the proteolysis sites of which had been well studied.