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Production of Disulfide-stabilized Transmembrane Peptide Complexes for Structural Studies
Published on: March 6, 2013
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.
Abstract:
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 αβ-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.
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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