期刊
BIOINFORMATICS
卷 37, 期 21, 页码 3723-3733出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btab628
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类别
资金
- VA Career Development Award [1 IK2 CX002049-01]
- Sunlin & Priscilla Chou Foundation
The study introduces a new open-source tool called pepsickle for proteasomal cleavage prediction, which has better performance and computational speed compared to current models, can predict sites based on protein profiles, and improves immune-responsive epitopes enrichment by post hoc filtering of predicted patient neoepitopes.
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. Supplementary information: Supplementary data are available at Bioinformatics online.
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