Exhaustive proteome mining for functional MHC-I ligands.
ACS Chem Biol
; 8(9): 1876-81, 2013 Sep 20.
Article
in En
| MEDLINE
| ID: mdl-23772559
ABSTRACT
We present the development and application of a new machine-learning approach to exhaustively and reliably identify major histocompatibility complex class I (MHC-I) ligands among all 20(8) octapeptides and in genome-derived proteomes of Mus musculus , influenza A H3N8, and vesicular stomatitis virus (VSV). Focusing on murine H-2K(b), we identified potent octapeptides exhibiting direct MHC-I binding and stabilization on the surface of TAP-deficient RMA-S cells. Computationally identified VSV-derived peptides induced CD8(+) T-cell proliferation after VSV-infection of mice. The study demonstrates that high-level machine-learning models provide a unique access to rationally designed peptides and a promising approach toward "reverse vaccinology".
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Oligopeptides
/
Genes, MHC Class I
/
H-2 Antigens
/
Vesiculovirus
/
Proteome
/
Influenza A Virus, H3N8 Subtype
Limits:
Animals
Language:
En
Journal:
ACS Chem Biol
Year:
2013
Type:
Article
Affiliation country:
Switzerland