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

The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.06.027805 doi: bioRxiv preprint population coverage, and a flag to indicate if the peptide sequence overlaps with any sequence in 1 the human proteome. The 10 HLA-I predicted binders with the broadest cumulative allele coverage. The table provides 5 the peptide sequence, its rank, the SARS-CoV-2 protein it is derived from, the alleles the peptide 6 is predicted to bind to and the cumulative HLA-I coverage for USA, European (EUR), and Asian The 10 SARS-CoV-2-derived 25mers with the broadest cumulative predicted HLA-II allele 19 coverage. For each 25mer, the table provides the rank, the peptide sequence, the SARS-CoV-2 20 protein it is derived from, the cumulative alleles that are covered by all 25mers up to this rank, 21 author/funder. All rights reserved. No reuse allowed without permission.