Author: Asaf Poran; Dewi Harjanto; Matthew Malloy; Michael S. Rooney; Lakshmi Srinivasan; Richard B. Gaynor
Title: Sequence-based prediction of vaccine targets for inducing T cell responses to SARS-CoV-2 utilizing the bioinformatics predictor RECON Document date: 2020_4_8
ID: 54mx8v4i_33
Snippet: In summary, our work provides the most robust set of both CD4 + and CD8 + T cells epitopes that 16 are spanning the entire SARS-CoV-2 genome and binding a wide set of HLA-I and HLA-II 17 alleles. Our predicted list of T cell epitopes serves as a resource for the scientific community to 18 generate potent SARS-CoV-2 vaccine epitopes and generate long-lasting T cell immunity. These 19 epitopes are predicted to bind MHC alleles covering over 99.9% o.....
Document: In summary, our work provides the most robust set of both CD4 + and CD8 + T cells epitopes that 16 are spanning the entire SARS-CoV-2 genome and binding a wide set of HLA-I and HLA-II 17 alleles. Our predicted list of T cell epitopes serves as a resource for the scientific community to 18 generate potent SARS-CoV-2 vaccine epitopes and generate long-lasting T cell immunity. These 19 epitopes are predicted to bind MHC alleles covering over 99.9% of the USA, European and 20 Asian Pacific Islander populations and could complement B cell epitopes that have been shown 21 to be effective but provide short-lived immunity. This expansive data set allows us to identify 22 author/funder. All rights reserved. No reuse allowed without permission.
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