Predicted Cellular Immunity Population Coverage Gaps for SARS-CoV-2 Subunit Vaccines and Their Augmentation by Compact Peptide Sets.
Cell Syst
; 12(1): 102-107.e4, 2021 01 20.
Article
in English
| MEDLINE | ID: covidwho-947149
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
Subunit vaccines induce immunity to a pathogen by presenting a component of the pathogen and thus inherently limit the representation of pathogen peptides for cellular immunity-based memory. We find that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) subunit peptides may not be robustly displayed by the major histocompatibility complex (MHC) molecules in certain individuals. We introduce an augmentation strategy for subunit vaccines that adds a small number of SARS-CoV-2 peptides to a vaccine to improve the population coverage of pathogen peptide display. Our population coverage estimates integrate clinical data on peptide immunogenicity in convalescent COVID-19 patients and machine learning predictions. We evaluate the population coverage of 9 different subunits of SARS-CoV-2, including 5 functional domains and 4 full proteins, and augment each of them to fill a predicted coverage gap.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Vaccines, Subunit
/
Machine Learning
/
COVID-19 Vaccines
/
COVID-19
/
Immunity, Cellular
Type of study:
Experimental Studies
/
Prognostic study
Topics:
Vaccines
Limits:
Humans
Language:
English
Journal:
Cell Syst
Year:
2021
Document Type:
Article
Affiliation country:
J.cels.2020.11.010
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