Literature DB >> 15557175

Transporter associated with antigen processing preselection of peptides binding to the MHC: a bioinformatic evaluation.

Irini Doytchinova1, Shelley Hemsley, Darren R Flower.   

Abstract

TAP is responsible for the transit of peptides from the cytosol to the lumen of the endoplasmic reticulum. In an immunological context, this event is followed by the binding of peptides to MHC molecules before export to the cell surface and recognition by T cells. Because TAP transport precedes MHC binding, TAP preferences may make a significant contribution to epitope selection. To assess the impact of this preselection, we have developed a scoring function for TAP affinity prediction using the additive method, have used it to analyze and extend the TAP binding motif, and have evaluated how well this model acts as a preselection step in predicting MHC binding peptides. To distinguish between MHC alleles that are exclusively dependent on TAP and those exhibiting only a partial dependence on TAP, two sets of MHC binding peptides were examined: HLA-A*0201 was selected as a representative of partially TAP-dependent HLA alleles, and HLA-A*0301 represented fully TAP-dependent HLA alleles. TAP preselection has a greater impact on TAP-dependent alleles than on TAP-independent alleles. The reduction in the number of nonbinders varied from 10% (TAP-independent) to 33% (TAP-dependent), suggesting that TAP preselection is an important component in the successful in silico prediction of T cell epitopes.

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Year:  2004        PMID: 15557175     DOI: 10.4049/jimmunol.173.11.6813

Source DB:  PubMed          Journal:  J Immunol        ISSN: 0022-1767            Impact factor:   5.422


  13 in total

1.  Characterizing the specificity and cooperation of aminopeptidases in the cytosol and endoplasmic reticulum during MHC class I antigen presentation.

Authors:  Arron Hearn; Ian A York; Courtney Bishop; Kenneth L Rock
Journal:  J Immunol       Date:  2010-03-29       Impact factor: 5.422

2.  Characterization of an human leucocyte antigen A2-restricted Epstein-Barr virus nuclear antigen-1-derived cytotoxic T-lymphocyte epitope.

Authors:  Diego Marescotti; Federica Destro; Anna Baldisserotto; Mauro Marastoni; Giuseppe Coppotelli; Maria Masucci; Riccardo Gavioli
Journal:  Immunology       Date:  2009-11-16       Impact factor: 7.397

3.  Cross-modality deep learning-based prediction of TAP binding and naturally processed peptide.

Authors:  Hanan Besser; Yoram Louzoun
Journal:  Immunogenetics       Date:  2018-02-28       Impact factor: 2.846

4.  TAP Hunter: a SVM-based system for predicting TAP ligands using local description of amino acid sequence.

Authors:  Tze Hau Lam; Hiroshi Mamitsuka; Ee Chee Ren; Joo Chuan Tong
Journal:  Immunome Res       Date:  2010-09-27

5.  The specificity of trimming of MHC class I-presented peptides in the endoplasmic reticulum.

Authors:  Arron Hearn; Ian A York; Kenneth L Rock
Journal:  J Immunol       Date:  2009-10-14       Impact factor: 5.422

6.  PRED(TAP): a system for prediction of peptide binding to the human transporter associated with antigen processing.

Authors:  Guang Lan Zhang; Nikolai Petrovsky; Chee Keong Kwoh; J Thomas August; Vladimir Brusic
Journal:  Immunome Res       Date:  2006-05-23

7.  Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models.

Authors:  Wen Liu; Xiangshan Meng; Qiqi Xu; Darren R Flower; Tongbin Li
Journal:  BMC Bioinformatics       Date:  2006-03-31       Impact factor: 3.169

8.  FRED--a framework for T-cell epitope detection.

Authors:  Magdalena Feldhahn; Pierre Dönnes; Philipp Thiel; Oliver Kohlbacher
Journal:  Bioinformatics       Date:  2009-07-04       Impact factor: 6.937

9.  MHCBN 4.0: A database of MHC/TAP binding peptides and T-cell epitopes.

Authors:  Sneh Lata; Manoj Bhasin; Gajendra P S Raghava
Journal:  BMC Res Notes       Date:  2009-04-20

10.  EpiJen: a server for multistep T cell epitope prediction.

Authors:  Irini A Doytchinova; Pingping Guan; Darren R Flower
Journal:  BMC Bioinformatics       Date:  2006-03-13       Impact factor: 3.169

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