Literature DB >> 8765039

Peptide binding specificity of major histocompatibility complex class I resolved into an array of apparently independent subspecificities: quantitation by peptide libraries and improved prediction of binding.

A Stryhn1, L O Pedersen, T Romme, C B Holm, A Holm, S Buus.   

Abstract

Considerable interest has focused on understanding how major histocompatibility complex (MHC) specificity is generated and characterizing the specificity of MHC molecules with the ultimate goal being to predict peptide binding. We have used a strategy where all possible peptides of a particular size are distributed into positional scanning combinatorial peptide libraries (PSCPL) to develop a highly efficient, universal and unbiased approach to address MHC specificity. The PSCPL approach appeared qualitatively and quantitatively superior to other currently used strategies. The average effect of any amino acid in each position was quantitated, allowing a detailed description of extended peptide binding motifs including primary and secondary anchor residues. It also identified disfavored residues which were found to be surprisingly important in shaping MHC class I specificity. Assuming that MHC class I specificity is the result of largely independently acting subsites, the binding of unknown peptides could be predicted. Conversely, this argues that MHC class I specificities consist of an array of subspecificities acting in a combinatorial mode.

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Year:  1996        PMID: 8765039     DOI: 10.1002/eji.1830260836

Source DB:  PubMed          Journal:  Eur J Immunol        ISSN: 0014-2980            Impact factor:   5.532


  34 in total

1.  Modeling the interactions of a peptide-major histocompatibility class I ligand with its receptors. I. Recognition by two alpha beta T cell receptors.

Authors:  D Rognan; A Stryhn; L Fugger; S Lyngbaek; J Engberg; P S Andersen; S Buus
Journal:  J Comput Aided Mol Des       Date:  2000-01       Impact factor: 3.686

2.  Reliable prediction of T-cell epitopes using neural networks with novel sequence representations.

Authors:  Morten Nielsen; Claus Lundegaard; Peder Worning; Sanne Lise Lauemøller; Kasper Lamberth; Søren Buus; Søren Brunak; Ole Lund
Journal:  Protein Sci       Date:  2003-05       Impact factor: 6.725

3.  Recovery of known T-cell epitopes by computational scanning of a viral genome.

Authors:  Antoine Logean; Didier Rognan
Journal:  J Comput Aided Mol Des       Date:  2002-04       Impact factor: 3.686

4.  Tapasin discriminates peptide-human leukocyte antigen-A*02:01 complexes formed with natural ligands.

Authors:  Gustav Roder; Linda Geironson; Michael Rasmussen; Mikkel Harndahl; Søren Buus; Kajsa Paulsson
Journal:  J Biol Chem       Date:  2011-04-25       Impact factor: 5.157

5.  Enhancement to the RANKPEP resource for the prediction of peptide binding to MHC molecules using profiles.

Authors:  Pedro A Reche; John-Paul Glutting; Hong Zhang; Ellis L Reinherz
Journal:  Immunogenetics       Date:  2004-09-03       Impact factor: 2.846

6.  Probing the specificity of binding to the major nuclear localization sequence-binding site of importin-alpha using oriented peptide library screening.

Authors:  Sundy N Y Yang; Agnes A S Takeda; Marcos R M Fontes; Jonathan M Harris; David A Jans; Bostjan Kobe
Journal:  J Biol Chem       Date:  2010-04-20       Impact factor: 5.157

Review 7.  Major histocompatibility complex class I binding predictions as a tool in epitope discovery.

Authors:  Claus Lundegaard; Ole Lund; Søren Buus; Morten Nielsen
Journal:  Immunology       Date:  2010-05-26       Impact factor: 7.397

8.  A combined prediction strategy increases identification of peptides bound with high affinity and stability to porcine MHC class I molecules SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01.

Authors:  Lasse Eggers Pedersen; Michael Rasmussen; Mikkel Harndahl; Morten Nielsen; Søren Buus; Gregers Jungersen
Journal:  Immunogenetics       Date:  2015-11-14       Impact factor: 2.846

9.  Identification of the peptide-binding motif recognized by the pigtail macaque class I MHC molecule Mane-A1*082:01 (Mane A*0301).

Authors:  Carrie Moore; John Sidney; A Michelle English; Amanda Wriston; Donald F Hunt; Jeffrey Shabanowitz; Scott Southwood; Kate Bradley; Bernard A P Lafont; Bianca R Mothé; Alessandro Sette
Journal:  Immunogenetics       Date:  2012-01-26       Impact factor: 2.846

10.  Proteomics in Vaccinology and Immunobiology: An Informatics Perspective of the Immunone.

Authors:  Irini A. Doytchinova; Paul Taylor; Darren R. Flower
Journal:  J Biomed Biotechnol       Date:  2003
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