Login / Signup

In Silico Defined SARS-CoV2 Epitopes May Not Predict Immunogenicity to COVID19.

Ke PanYulun ChiuMichelle ChenJunmei WangIvy LaiShailbala SinghRebecca ShawCassian Yee
Published in: bioRxiv : the preprint server for biology (2021)
SARS-CoV-2 infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID19, the disease caused by SARS-CoV-2, it has become increasingly apparent that T cell responses are equally, if not more important than humoral responses in mediating recovery and immune-protection. One of the major challenges in developing T cell-based therapies for infectious and malignant diseases has been the identification of immunogenic epitopes that can elicit a meaningful T cell response. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes deduced from binding affinities and consensus data. Our studies find that, in contrast to current dogma, 'immunodominant' SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing naturally presented SARS-CoV-2 epitopes.
Keyphrases
  • sars cov
  • immune response
  • respiratory syndrome coronavirus
  • molecular docking
  • magnetic resonance
  • coronavirus disease
  • dendritic cells
  • magnetic resonance imaging
  • machine learning
  • transcription factor
  • dna binding