Literature DB >> 12646688

HLA-A3 supermotif defined by quantitative structure-activity relationship analysis.

Pingping Guan1, Irini A Doytchinova, Darren R Flower.   

Abstract

Activation of a cytotoxic T cell requires specific binding of antigenic peptides to major histocompatibility complex (MHC) molecules. This paper reports a study of peptides binding to members of the HLA-A3 superfamily using a recently developed 2D-QSAR method, called the additive method. Four alleles with high phenotype frequency were included in the study: A*0301, A*1101, A*3101 and A*6801. The influence of each of the 20 amino acids at each position of the peptide on binding was studied. A refined A3 supertype motif was defined in the study.

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Year:  2003        PMID: 12646688     DOI: 10.1093/proeng/gzg005

Source DB:  PubMed          Journal:  Protein Eng        ISSN: 0269-2139


  13 in total

1.  Structural and energetic evidence for highly peptide-specific tumor antigen targeting via allo-MHC restriction.

Authors:  Amy A Simpson; Fiyaz Mohammed; Mahboob Salim; Amy Tranter; Alan B Rickinson; Hans J Stauss; Paul A H Moss; Neil M Steven; Benjamin E Willcox
Journal:  Proc Natl Acad Sci U S A       Date:  2011-12-12       Impact factor: 11.205

2.  Robust quantitative modeling of peptide binding affinities for MHC molecules using physical-chemical descriptors.

Authors:  Ovidiu Ivanciuc; Werner Braun
Journal:  Protein Pept Lett       Date:  2007       Impact factor: 1.890

3.  Identification of three novel CTL epitopes within nucleocapsid protein of Hantaan virus.

Authors:  Meiliang Wang; Yong Zhu; Jiuping Wang; Tongde Lv; Boquan Jin
Journal:  Viral Immunol       Date:  2011-11-23       Impact factor: 2.257

4.  MHCPred: A server for quantitative prediction of peptide-MHC binding.

Authors:  Pingping Guan; Irini A Doytchinova; Christianna Zygouri; Darren R Flower
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

5.  AntiJen: a quantitative immunology database integrating functional, thermodynamic, kinetic, biophysical, and cellular data.

Authors:  Christopher P Toseland; Debra J Clayton; Helen McSparron; Shelley L Hemsley; Martin J Blythe; Kelly Paine; Irini A Doytchinova; Pingping Guan; Channa K Hattotuwagama; Darren R Flower
Journal:  Immunome Res       Date:  2005-10-06

6.  HLA class I supertypes: a revised and updated classification.

Authors:  John Sidney; Bjoern Peters; Nicole Frahm; Christian Brander; Alessandro Sette
Journal:  BMC Immunol       Date:  2008-01-22       Impact factor: 3.615

7.  Personalized adoptive immunotherapy for patients with EBV-associated tumors and complications: Evaluation of novel naturally processed and presented EBV-derived T-cell epitopes.

Authors:  Maren Bieling; Sabine Tischer; Ulrich Kalinke; Rainer Blasczyk; Søren Buus; Britta Maecker-Kolhoff; Britta Eiz-Vesper
Journal:  Oncotarget       Date:  2017-12-21

8.  Deep convolutional neural networks for pan-specific peptide-MHC class I binding prediction.

Authors:  Youngmahn Han; Dongsup Kim
Journal:  BMC Bioinformatics       Date:  2017-12-28       Impact factor: 3.169

9.  Integrating in silico and in vitro analysis of peptide binding affinity to HLA-Cw*0102: a bioinformatic approach to the prediction of new epitopes.

Authors:  Valerie A Walshe; Channa K Hattotuwagama; Irini A Doytchinova; Mailee Wong; Isabel K Macdonald; Arend Mulder; Frans H J Claas; Pierre Pellegrino; Jo Turner; Ian Williams; Emma L Turnbull; Persephone Borrow; Darren R Flower
Journal:  PLoS One       Date:  2009-11-30       Impact factor: 3.240

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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