Peptide-Binding Groove Contraction Linked to the Lack of T Cell Response: Using Complex Structure and Energy To

Yuan-Ping Pang1, Laura R Elsbernd2, Matthew S Block2,3

  • 1Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN 55905; pang@mayo.edu.

Immunohorizons
|April 26, 2019
PubMed

Insights

Personalized peptide vaccines (PPVs) show promise for cancer treatment. A new computational method, SEFF12MC, accurately predicts peptide immunogenicity by analyzing HLA complex structure, improving neoantigen identification for PPVs.

Area of Science:

  • Immunology
  • Computational Biology
  • Structural Biology

Background:

  • Personalized peptide vaccines (PPVs) target tumor neoantigens for cancer immunotherapy.
  • Current in silico methods for neoantigen identification have limited effectiveness.
  • Identifying immunogenic peptides is crucial for successful PPV development.

Purpose of the Study:

  • To investigate the structural basis of peptide-HLA (human leukocyte antigen) interactions and T cell receptor recognition.
  • To develop a novel computational method for predicting peptide immunogenicity.
  • To improve the identification of effective neoantigens for personalized cancer vaccines.

Main Methods:

  • Molecular dynamics simulations of 12 oligopeptides bound to HLA molecules.
  • Conformational analysis of peptide-HLA complexes and their interaction with T cell receptors (TCRs).
  • Development and application of an atom-based immunogenicity prediction method (SEFF12MC).

Main Results:

  • A novel association was found between HLA groove contraction upon peptide binding and lack of T cell response.
  • This contraction causes incompatibility at the peptide-HLA/TCR interface, impacting immunogenicity.
  • The SEFF12MC method achieved 100% accuracy in predicting the immunogenicity of 12 oligopeptides.
  • SEFF12MC outperformed existing residue-based methods (25-50% success rate).

Conclusions:

  • Peptide binding to HLA does not guarantee immunogenicity; structural compatibility with TCR is essential.
  • The SEFF12MC method offers a more accurate approach to predicting peptide immunogenicity.
  • This advancement could overcome hurdles in developing personalized cancer immunotherapies using patient tumor DNA.

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