Many pharmaceutical companies are focusing on whole-pathogen vaccines, which are time-tested but may produce adverse effects in recipients. Alternatively, peptide-based vaccines have emerged as faster, safer, and more effective therapeutics because they target antigen-presenting cells (APC), removing the need for processing, and can be quickly designed bioinformatically and synthesized. This in silico design strategy involves processing and binding predictions for both cytotoxic and helper T-cells; each of these viral peptide interaction tools can be found on the NIH-funded Immune Epitope Database (IEDB). The identified peptides, or epitopes, are 9-12 amino acids long and can elicit an immune response from T-cells based on their binding affinity with the APC’s major histocompatibility complex. The efficacy of vaccines can be further increased by targeting non-structural proteins, which have lesser mutation rates than the traditional target, binding glycoproteins. This project aimed to use this knowledge to create a more efficacious coronavirus vaccine.
Evaluate the utility of non-structural proteins in peptide-based vaccine design
Learn how to use bioinformatic tool to design more immunodominant epitopes for vaccine
Recognize efficiency of peptide-based vaccine design in the context of a pandemic