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

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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.

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About the authors

E. V. Matveev

Skolkovo Institute of Science and Technology; Kharkevich Institute for Information Transmission Problem; Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology

Email: mkazanov@gmail.com
Russian Federation, Moscow, 121205; Moscow, 127051; Moscow, 117997

G. V. Ponomarev

Skolkovo Institute of Science and Technology; Kharkevich Institute for Information Transmission Problem

Email: mkazanov@gmail.com
Russian Federation, Moscow, 121205; Moscow, 127051

M. D. Kazanov

Skolkovo Institute of Science and Technology; Kharkevich Institute for Information Transmission Problem; Dmitry Rogachev National Medical Research Center of Pediatric Hematology, Oncology and Immunology

Author for correspondence.
Email: mkazanov@gmail.com
Russian Federation, Moscow, 121205; Moscow, 127051; Moscow, 117997

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Supplementary files

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2. Fig. 1. Assessment of the proteolytic efficiency of human proteases relative to the SARS-CoV-2 S-glycoprotein sites. Human proteolytic enzymes with the highest CS values at position R815 of the S2’ site (a) and at position R685 of the S1/S2 site (b). Distribution of CS values for known proteolytic sites and randomly selected positions (c).

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3. Fig.. 2. Assessment of proteolytic accessibility of SARS-CoV-2 S-glycoprotein sites. a ‒ Display on the structure of S-glycoprotein (PDB ID: 6VXX) estimates of proteolytic accessibility in the region of the S2’ site (position R815). b - Display on the structure of S-glycoprotein of estimates of proteolytic accessibility in the region of the S1/S2 site (position R685). The color gradient from blue to red to yellow corresponds to changes from a minimum proteolytic accessibility score of 0 to a maximum of 1.

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