In Silico Analysis of Single Nucleotide Polymorphisms Related to Susceptibility and Severity in COVID-19 Patients

Abstract

Coronavirus disease 2019 (COVID-19) is a respiratory tract symptoms caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which exhibits a wide range of symptoms, from mild to severe. Genetic factors play a significant role in determining severity of the symptoms. Specifically, certain variants within genes can predispose individuals to experience severe COVID-19 symptoms. Therefore, this study aims to analyze these variants, also known as single nucleotide polymorphisms (SNP) within the ABO, TMPRSS2, ACE2, PAI-1, and IFNAR2 genes. The in silico method was used based on internet sites and software to identify the level of SNP pathogenicity, stability, visualization of 3-dimensional protein structures, and figures of amino acid changes as well as to analyze the pathomechanism of variants that lead to susceptibility or severe symptoms of COVID-19 patients. The results showed that the presence of SNP influences changes in the structure or stability of proteins, and the 3-dimensional structure of all proteins affected by SNP was successfully visualized. Based on pathomechanism analysis and amino acid structure of F216I and P74S protein ABO residues, V160M protein TMPRSS2, I468V, and K26R protein ACE2 are associated with susceptibility of the patient to SARS-CoV-2 infection. In addition, the results of the in silico analysis showed that A15T residues of PAI-1 protein, F10V, and F8S IFNAR2 protein were included with pathomechanisms leading to severe symptoms of COVID-19.