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The copyright holder for this preprint (which was not peer-reviewed) is the .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 from any alleles that have already been selected (Supplementary Table 5 ). This second list was 1 used to generate Figure 3A . To identify HLA-II epitopes, we used RECON's HLA-II binding predictor to score all 12-20mer 4 sequences in the SARS-CoV-2 proteome to predict both binding potential and the likely binding Table 2 ). 8 Peptide/allele pairs were assigned a percent rank by comparing their binding scores to those of 9 100,000 reference peptides. Pairs scoring in the top 1% were deemed likely to bind. 10 Additionally, we define the "epitope" of a 12-20mer to be the predicted binding core within the 11 sequence. As such, overlapping 12-20mers with the same predicted binding core for a given 12 allele would constitute a single epitope. Table 1 shows counts of these epitopes.