Mapping Immunogenic Regions in SARS-CoV-2 Variants to Understand Vaccine Design Using Bioinformatics Tools

Location

SU-003

Start Date

28-4-2023 10:00 AM

Department

Biology

Abstract

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a virus that causes the respiratory disease, COVID-19. Identifying antigenic determinants that bind to antibodies is important for designing peptide-based vaccines that are reliable and effective. Spike glycoproteins of SARS-CoV-2 are responsible for attachment and entry into a cell. The S1 subunit of the spike glycoprotein contains a receptor-binding domain that binds to angiotensin-converting enzyme 2 (ACE2) which facilitates viral entry into a cell. The ACE2 receptor is expressed on the ciliated epithelium of the upper and lower respiratory tract, macrophages, mast cells, and vascular endothelial cells. It is widely recognized that the respiratory symptoms of COVID-19 range from minimal to significant hypoxia. SARS-CoV-2 has accumulated many mutations within the last two years resulting in different variants. Developing mutations can increase pathogenicity and virulence thereby reducing the efficacy of vaccines and challenging adaptive immunity. Identifying epitopes in different variants with appropriate immunogenicity is important for a robust vaccine design. In this study, we will map the immunogenic regions on the spike glycoproteins of the SARS-CoV-2 variants Alpha, Beta, Gamma, Delta, and Omicron. Using the web-based bioinformatics platform Immune Epitope Database (iedb.org) which is funded by NIAID (National Institute of Allergy and Infectious Diseases), we have identified the amino acid residues located on the immunogenic regions of the spike glycoprotein of SARS-CoV-2. The IEDB, www.iedb.org, contains published epitope information and prediction tools that can be used as a research platform for studying infectious diseases, and it hosts an enhanced 3D viewer using NCBI’s iCn3D viewer. We will use these tools to predict immune evasion of the five variants of concern B.1.1.7 and B.1.351, P.1, B.1.617.2, B.1.1.529, Alpha, Beta, Gamma, Delta, and Omicron, respectively. Analysis of these immune epitope queries will assist in suggesting future candidates for peptide-based vaccines.

Faculty Sponsor

Sheela Vemu, Waubonsee Community College

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Apr 28th, 10:00 AM

Mapping Immunogenic Regions in SARS-CoV-2 Variants to Understand Vaccine Design Using Bioinformatics Tools

SU-003

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a virus that causes the respiratory disease, COVID-19. Identifying antigenic determinants that bind to antibodies is important for designing peptide-based vaccines that are reliable and effective. Spike glycoproteins of SARS-CoV-2 are responsible for attachment and entry into a cell. The S1 subunit of the spike glycoprotein contains a receptor-binding domain that binds to angiotensin-converting enzyme 2 (ACE2) which facilitates viral entry into a cell. The ACE2 receptor is expressed on the ciliated epithelium of the upper and lower respiratory tract, macrophages, mast cells, and vascular endothelial cells. It is widely recognized that the respiratory symptoms of COVID-19 range from minimal to significant hypoxia. SARS-CoV-2 has accumulated many mutations within the last two years resulting in different variants. Developing mutations can increase pathogenicity and virulence thereby reducing the efficacy of vaccines and challenging adaptive immunity. Identifying epitopes in different variants with appropriate immunogenicity is important for a robust vaccine design. In this study, we will map the immunogenic regions on the spike glycoproteins of the SARS-CoV-2 variants Alpha, Beta, Gamma, Delta, and Omicron. Using the web-based bioinformatics platform Immune Epitope Database (iedb.org) which is funded by NIAID (National Institute of Allergy and Infectious Diseases), we have identified the amino acid residues located on the immunogenic regions of the spike glycoprotein of SARS-CoV-2. The IEDB, www.iedb.org, contains published epitope information and prediction tools that can be used as a research platform for studying infectious diseases, and it hosts an enhanced 3D viewer using NCBI’s iCn3D viewer. We will use these tools to predict immune evasion of the five variants of concern B.1.1.7 and B.1.351, P.1, B.1.617.2, B.1.1.529, Alpha, Beta, Gamma, Delta, and Omicron, respectively. Analysis of these immune epitope queries will assist in suggesting future candidates for peptide-based vaccines.