pepsickle rapidly and accurately predicts proteasomal cleavage sites for improved neoantigen identification

Benjamin R. Weeder, Mary A. Wood, Ellysia Li, Abhinav Nellore, Reid F. Thompson

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Motivation: Proteasomal cleavage is a key component in protein turnover, as well as antigen processing and presentation. Although tools for proteasomal cleavage prediction are available, they vary widely in their performance, options and availability. Results: Herein, we present pepsickle, an open-source tool for proteasomal cleavage prediction with better in vivo prediction performance (area under the curve) and computational speed than current models available in the field and with the ability to predict sites based on both constitutive and immunoproteasome profiles. Post hoc filtering of predicted patient neoepitopes using pepsickle significantly enriches for immune-responsive epitopes and may improve current epitope prediction and vaccine development pipelines.

Original languageEnglish (US)
Pages (from-to)3723-3733
Number of pages11
JournalBioinformatics
Volume37
Issue number21
DOIs
StatePublished - Nov 1 2021

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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