Journal
ACS CHEMICAL BIOLOGY
Volume 8, Issue 9, Pages 1876-1881Publisher
AMER CHEMICAL SOC
DOI: 10.1021/cb400252t
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Funding
- ETH Zurich
- Swiss National Science Foundation (SNF) [205321-134783]
- Deutsche Forschungsgemeinschaft (DFG) [SFB 852]
- BMBF [13N9197, 13N11455]
- EU-FP7 (LEISHDNAVAX)
- DAAD, Germany
- FAPESP, Brazil
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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.
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