Using personalized peptide vaccines (PPVs) to target tumor-specific nonself-antigens (neoantigens) is a promising approach to cancer treatment. However, the development of PPVs is hindered by the challenge of identifying tumor-specific neoantigens, in part because current in silico methods for identifying such neoantigens have limited effectiveness. In this article, we report the results of molecular dynamics simulations of 12 oligopeptides bound with an HLA, revealing a previously unrecognized association between the inability of an oligopeptide to elicit a T cell response and the contraction of the peptide-binding groove upon binding of the oligopeptide to the HLA. Our conformational analysis showed that this association was due to incompatibility at the interface between the contracted groove and its ab–T cell Ag receptor. This structural demonstration that having the capability to bind HLA does not guarantee immunogenicity prompted us to develop an atom-based method (SEFF12MC) to predict immunogenicity through using the structure and energy of a peptide×HLA complex to assess the propensity of the complex for further complexation with its TCR. In predicting the immunogenicities of the 12 oligopeptides, SEFF12MC achieved a 100% success rate, compared with success rates of 25–50% for 11 publicly available residue-based methods including NetMHC-4.0. Although further validation and refinements of SEFF12MC are required, our results suggest a need to develop in silico methods that assess peptide characteristics beyond their capability to form stable binary complexes with HLAs to help remove hurdles in using the patient tumor DNA information to develop PPVs for personalized cancer immunotherapy.
ASJC Scopus subject areas
- Immunology and Allergy