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Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

Fagerberg, Theres; Zoete, Vincent; Viatte, Sebastien; Baumgaertner, Petra; Alves, Pedro M; Romero, Pedro; Speiser, Daniel E; Michielin, Olivier

PloS one. 2013;8(7):e65590.

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Abstract

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Bibliographic metadata

Type of resource:
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Publication status:
Published
Publication type:
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Published date:
Language:
eng
Journal title:
Abbreviated journal title:
ISSN:
Place of publication:
United States
Volume:
8
Issue:
7
Pagination:
e65590
Digital Object Identifier:
10.1371/journal.pone.0065590
Pubmed Identifier:
23874382
Pii Identifier:
PONE-D-13-07736
Attached files embargo period:
Immediate release
Attached files release date:
9th October, 2014
Access state:
Active

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Record metadata

Manchester eScholar ID:
uk-ac-man-scw:236587
Created by:
Ingram, Mary
Created:
9th October, 2014, 14:45:28
Last modified by:
Ingram, Mary
Last modified:
9th October, 2014, 15:03:02

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