Analysis of Seven Human Respiratory Coronavirus (CoV) S Proteins from a Bioinformatics Approach

Abstract

The coronavirus disease 2019 (COVID-19) has caused a huge pandemic repercussion across the globe and it is mainly contributed by the human severe acute respiratory syndrome coronavirus (SARS-CoV-2). There are seven human respiratory coronaviruses identified to date, namely HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1, MERS-CoV, SARS-CoV and SARS-CoV-2. A recently published bioinformatic human CoV comparison only covered four human CoV. Therefore, in this study, a bioinformatics approach-based analyses route was taken to dissect the S proteins of all the available (seven) human respiratory coronaviruses publicly available in the GenBank database. The antigenic epitope amount is postulated to be the most accurate bioindicator among all in determining the severity of a particular human respiratory coronavirus. Other powerful bioinformatic indicators are global similarity index, maximum likelihood phylogenetic analysis as well as domain analysis. The data generated in this study can be channelled to the vaccine and antiviral drug development to combat the current and future spread of the human respiratory coronaviruses.