@article{a700fe74cdb543568cd4af2c54ad2b47,
title = "Peptide-Binding Groove Contraction Linked to the Lack of T Cell Response: Using Complex Structure and Energy To Identify Neoantigens",
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 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.",
author = "Pang, {Yuan Ping} and Elsbernd, {Laura R.} and Block, {Matthew S.} and Markovic, {Svetomir N.}",
note = "Funding Information: Received for publication July 11, 2018. Accepted for publication July 23, 2018. Address correspondence and reprint requests to: Prof. Yuan-Ping Pang, Stabile 12-26, Mayo Clinic, 200 First Street SW, Rochester, MN 55905. E-mail address: pang@ mayo.edu ORCIDs: 0000-0003-0838-2560 (Y.-P.P.); 0000-0003-3967-921X (L.R.E.); 0000-0001-5692-4219 (M.S.B.). S.N.M., M.S.B., and L.R.E. designed the overall immunogenicity prediction study using peptides derived from B-Raf and CMV proteins; Y.-P.P. conceived and implemented SEFF12MC and performed the immunogenicity prediction study using SEFF12MC. L.R.E. performed the immunogenicity prediction study using 11 residue-based methods; Y.-P.P. and L.R.E. analyzed all prediction data; Y.-P.P. wrote the paper; all authors contributed revisions. This work was supported by the U.S. Army Research Office (W911NF-16-1-0264 to Y.-P.P.), the 2014 Mayo Clinic Center for Multiple Sclerosis and Demyelinating Diseases award (FP00078307 to Y.-P.P.), the Mayo Foundation for Medical Education and Research, the Mayo Clinic Graduate School of Biomedical Sciences (to L.R.E.), and the Mayo Immunology Ph.D. Training Program (to L.R.E.). The content of this article is the sole responsibility of the authors and does not represent the official views of the funders. Abbreviations used in this article: CaRMSD, Ca root mean square deviation; HLA-A2, HLA A*02:01; ID, identifier; MD, molecular dynamics; PDB, Protein Data Bank; PPV, personalized peptide vaccine; SR, success rate. The online version of this article contains supplemental material. This article is distributed under the terms of the CC BY 4.0 Unported license. Copyright {\textcopyright} 2018 The Authors Publisher Copyright: Copyright {\textcopyright} 2018 The Authors",
year = "2018",
month = aug,
day = "1",
doi = "10.4049/immunohorizons.1800048",
language = "English (US)",
volume = "2",
pages = "216--225",
journal = "ImmunoHorizons",
issn = "2573-7732",
publisher = "NLM (Medline)",
number = "7",
}