MHCflurry 2.0: Improved Pan-Allele Prediction of MHC Class I-Presented Peptides by Incorporating Antigen Processing

Tim O’Donnell, Alex Rubinsteyn, Uri Laserson

Extension of our peptide-MHC binding predictor MHCflurry to explicitly consider allele-invariant sequence motifs that correspond to signatures of antigen processing by the proteasome, TAP, and ERAP. The antigen processing score is combined with an allele specific MHC affinity score to derive a combined presentation score.


Landscape and Selection of Vaccine Epitopes in SARS-CoV-2

Christof C. Smith, Sarah Entwistle, Caryn Willis, Steven Vensko, Wolfgang Beck, Jason Garness, Maria Sambade, Eric Routh, Kelly Olsen, Julia Kodysh, Timothy O’Donnell, Carsten Haber, Kirsten Heiss, Volker Stadler, Erik Garrison, Oliver C. Grant, Robert J. Woods, Mark Heise, Benjamin G. Vincent, Alex Rubinsteyn

We combine computational prediction of T cell epitopes, recently published B cell epitope mapping studies, and epitope accessibility to select candidate peptide vaccines for SARS-CoV-2. In addition to predicted MHC affinity, candidate T cell epitopes were refined by predicted immunogenicity, viral source protein abundance, sequence conservation, coverage of high frequency HLA alleles and co-localization of CD4+ and CD8+ T cell epitopes. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering to select regions with surface accessibility, high sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. By combining B cell and T cell analyses, as well as a manufacturability heuristic, we propose a set of SARS-CoV-2 vaccine peptides for use in subsequent murine studies and clinical trials.