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Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition

Accurate predictions of T-cell epitopes would be useful for designing vaccines, immunotherapies for cancer and autoimmune diseases, and improved protein therapies. The humoral immune response involves uptake of antigens by antigen presenting cells (APCs), APC processing and presentation of peptides...

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Autores principales: Schneidman-Duhovny, Dina, Khuri, Natalia, Dong, Guang Qiang, Winter, Michael B., Shifrut, Eric, Friedman, Nir, Craik, Charles S., Pratt, Kathleen P., Paz, Pedro, Aswad, Fred, Sali, Andrej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219782/
https://www.ncbi.nlm.nih.gov/pubmed/30399156
http://dx.doi.org/10.1371/journal.pone.0206654
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author Schneidman-Duhovny, Dina
Khuri, Natalia
Dong, Guang Qiang
Winter, Michael B.
Shifrut, Eric
Friedman, Nir
Craik, Charles S.
Pratt, Kathleen P.
Paz, Pedro
Aswad, Fred
Sali, Andrej
author_facet Schneidman-Duhovny, Dina
Khuri, Natalia
Dong, Guang Qiang
Winter, Michael B.
Shifrut, Eric
Friedman, Nir
Craik, Charles S.
Pratt, Kathleen P.
Paz, Pedro
Aswad, Fred
Sali, Andrej
author_sort Schneidman-Duhovny, Dina
collection PubMed
description Accurate predictions of T-cell epitopes would be useful for designing vaccines, immunotherapies for cancer and autoimmune diseases, and improved protein therapies. The humoral immune response involves uptake of antigens by antigen presenting cells (APCs), APC processing and presentation of peptides on MHC class II (pMHCII), and T-cell receptor (TCR) recognition of pMHCII complexes. Most in silico methods predict only peptide-MHCII binding, resulting in significant over-prediction of CD4 T-cell epitopes. We present a method, ITCell, for prediction of T-cell epitopes within an input protein antigen sequence for given MHCII and TCR sequences. The method integrates information about three stages of the immune response pathway: antigen cleavage, MHCII presentation, and TCR recognition. First, antigen cleavage sites are predicted based on the cleavage profiles of cathepsins S, B, and H. Second, for each 12-mer peptide in the antigen sequence we predict whether it will bind to a given MHCII, based on the scores of modeled peptide-MHCII complexes. Third, we predict whether or not any of the top scoring peptide-MHCII complexes can bind to a given TCR, based on the scores of modeled ternary peptide-MHCII-TCR complexes and the distribution of predicted cleavage sites. Our benchmarks consist of epitope predictions generated by this algorithm, checked against 20 peptide-MHCII-TCR crystal structures, as well as epitope predictions for four peptide-MHCII-TCR complexes with known epitopes and TCR sequences but without crystal structures. ITCell successfully identified the correct epitopes as one of the 20 top scoring peptides for 22 of 24 benchmark cases. To validate the method using a clinically relevant application, we utilized five factor VIII-specific TCR sequences from hemophilia A subjects who developed an immune response to factor VIII replacement therapy. The known HLA-DR1-restricted factor VIII epitope was among the six top-scoring factor VIII peptides predicted by ITCall to bind HLA-DR1 and all five TCRs. Our integrative approach is more accurate than current single-stage epitope prediction algorithms applied to the same benchmarks. It is freely available as a web server (http://salilab.org/itcell).
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spelling pubmed-62197822018-11-19 Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition Schneidman-Duhovny, Dina Khuri, Natalia Dong, Guang Qiang Winter, Michael B. Shifrut, Eric Friedman, Nir Craik, Charles S. Pratt, Kathleen P. Paz, Pedro Aswad, Fred Sali, Andrej PLoS One Research Article Accurate predictions of T-cell epitopes would be useful for designing vaccines, immunotherapies for cancer and autoimmune diseases, and improved protein therapies. The humoral immune response involves uptake of antigens by antigen presenting cells (APCs), APC processing and presentation of peptides on MHC class II (pMHCII), and T-cell receptor (TCR) recognition of pMHCII complexes. Most in silico methods predict only peptide-MHCII binding, resulting in significant over-prediction of CD4 T-cell epitopes. We present a method, ITCell, for prediction of T-cell epitopes within an input protein antigen sequence for given MHCII and TCR sequences. The method integrates information about three stages of the immune response pathway: antigen cleavage, MHCII presentation, and TCR recognition. First, antigen cleavage sites are predicted based on the cleavage profiles of cathepsins S, B, and H. Second, for each 12-mer peptide in the antigen sequence we predict whether it will bind to a given MHCII, based on the scores of modeled peptide-MHCII complexes. Third, we predict whether or not any of the top scoring peptide-MHCII complexes can bind to a given TCR, based on the scores of modeled ternary peptide-MHCII-TCR complexes and the distribution of predicted cleavage sites. Our benchmarks consist of epitope predictions generated by this algorithm, checked against 20 peptide-MHCII-TCR crystal structures, as well as epitope predictions for four peptide-MHCII-TCR complexes with known epitopes and TCR sequences but without crystal structures. ITCell successfully identified the correct epitopes as one of the 20 top scoring peptides for 22 of 24 benchmark cases. To validate the method using a clinically relevant application, we utilized five factor VIII-specific TCR sequences from hemophilia A subjects who developed an immune response to factor VIII replacement therapy. The known HLA-DR1-restricted factor VIII epitope was among the six top-scoring factor VIII peptides predicted by ITCall to bind HLA-DR1 and all five TCRs. Our integrative approach is more accurate than current single-stage epitope prediction algorithms applied to the same benchmarks. It is freely available as a web server (http://salilab.org/itcell). Public Library of Science 2018-11-06 /pmc/articles/PMC6219782/ /pubmed/30399156 http://dx.doi.org/10.1371/journal.pone.0206654 Text en © 2018 Schneidman-Duhovny et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Schneidman-Duhovny, Dina
Khuri, Natalia
Dong, Guang Qiang
Winter, Michael B.
Shifrut, Eric
Friedman, Nir
Craik, Charles S.
Pratt, Kathleen P.
Paz, Pedro
Aswad, Fred
Sali, Andrej
Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition
title Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition
title_full Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition
title_fullStr Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition
title_full_unstemmed Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition
title_short Predicting CD4 T-cell epitopes based on antigen cleavage, MHCII presentation, and TCR recognition
title_sort predicting cd4 t-cell epitopes based on antigen cleavage, mhcii presentation, and tcr recognition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219782/
https://www.ncbi.nlm.nih.gov/pubmed/30399156
http://dx.doi.org/10.1371/journal.pone.0206654
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