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Hypothesis and Theory ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Immunol. | doi: 10.3389/fimmu.2019.02731

Analysis of secondary structure biases in naturally presented HLA-I ligands

  • 1Department of Oncology, Université de Lausanne, Switzerland
  • 2Swiss Institute of Bioinformatics (SIB), Switzerland
  • 3Department of Oncology (CHUV), Switzerland
  • 4Human Integrated Tumor Immunology Discovery Engine, Department of Oncology, Ludwig Institute for Cancer Research, University Hospital of Lausanne, Switzerland

Recent clinical developments in antitumor immunotherapy involving T-cell related therapeutics have led to a renewed interest for human leukocyte antigen class I (HLA-I) binding peptides, given their potential use as peptide vaccines. Databases of HLA-I binding peptides hold therefore information on therapeutic targets essential for understanding immunity.
In this work, we use in depth and accurate HLA-I peptidomics datasets determined by mass-spectrometry (MS) and analyse properties of the HLA-I binding peptides with structure-based computational approaches. HLA-I binding peptides are studied grouping all alleles together or in allotype-specific contexts. We capitalize on the increasing number of structurally determined proteins to (1) map the 3D structure of HLA-I binding peptides into the source proteins for analysing their secondary structure and solvent accessibility in the protein context, and (2) search for potential differences between these properties in HLA-I binding peptides and in a reference dataset of HLA-I motif-like peptides. This is performed by an in-house developed heuristic search that considers peptides across all the human proteome and converges to a collection of peptides that exhibit exactly the same motif as the HLA-I peptides.
Our results, based on 9-mers matched to protein 3D structures, clearly show enriched sampling for HLA-I presentation of helical fragments in the source proteins. This enrichment is significant, as compared to 9-mer HLA-I motif-like peptides, and is not entirely explained by the helical propensity of the preferred residues in the HLA-I motifs. We give possible hypothesis for the secondary structure biases observed in HLA-I peptides. This contribution is of potential interest for researchers working in the field of antigen presentation and proteolysis. This knowledge refines the understanding of the rules governing antigen presentation and could be added to the parameters of the current peptide-MHC class I binding predictors to increase their antigen predictive ability.

Keywords: human leukocyte antigen (HLA), computational immunology, three-dimensional structures, HLA-I, HLA-I motif like peptides, HLA-I ligand presentation , Heuristic search algorithm

Received: 18 Feb 2019; Accepted: 07 Nov 2019.

Copyright: © 2019 Perez, Bassani-Sternberg, Coukos, Gfeller and Zoete. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Vincent Zoete, Université de Lausanne, Department of Oncology, Lausanne, Switzerland,