Sequence-based prediction of vaccine targets for inducing T cell responses to SARS-CoV-2 utilizing the bioinformatics predictor RECON

Asaf Poran; Dewi Harjanto; Matthew Malloy; Michael S. Rooney; Lakshmi Srinivasan; Richard B. Gaynor

In this work, we demonstrated the utility and validity of our HLA-I and HLA-II binding 16 prediction algorithms to the Coronaviridae virus family, and specifically to SARS-CoV-2. By 17 applying these algorithms to previously assayed peptide-MHC allele pairs in ViPR, we were able 18 to show excellent concordance between our binding predictions and the results of the assays for 19 both HLA-I and HLA-II epitopes. We leveraged the homology within the Coronaviridae family 20 to demonstrate that an exceedingly high portion (~90%) of our high-ranking SARS-CoV-2 21 peptide-MHC allele pairs for which validation was available was indeed confirmed to bind the 22 predicted MHC allele. Likewise, lowly-scoring peptide-MHC allele pairs derived from SARS-23 author/funder. All rights reserved. No reuse allowed without permission.