Literature DB >> 27624584

Prediction of peptide binding to a major histocompatibility complex class I molecule based on docking simulation.

Takeshi Ishikawa1.   

Abstract

Binding between major histocompatibility complex (MHC) class I molecules and immunogenic epitopes is one of the most important processes for cell-mediated immunity. Consequently, computational prediction of amino acid sequences of MHC class I binding peptides from a given sequence may lead to important biomedical advances. In this study, an efficient structure-based method for predicting peptide binding to MHC class I molecules was developed, in which the binding free energy of the peptide was evaluated by two individual docking simulations. An original penalty function and restriction of degrees of freedom were determined by analysis of 361 published X-ray structures of the complex and were then introduced into the docking simulations. To validate the method, calculations using a 50-amino acid sequence as a prediction target were performed. In 27 calculations, the binding free energy of the known peptide was within the top 5 of 166 peptides generated from the 50-amino acid sequence. Finally, demonstrative calculations using a whole sequence of a protein as a prediction target were performed. These data clearly demonstrate high potential of this method for predicting peptide binding to MHC class I molecules.

Keywords:  Degrees of freedom restriction; Docking simulation; Major histocompatibility complex class I molecule; Penalty function; Structure-based method; X-ray structure analysis

Mesh:

Substances:

Year:  2016        PMID: 27624584     DOI: 10.1007/s10822-016-9967-3

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  48 in total

1.  Different length peptides bind to HLA-Aw68 similarly at their ends but bulge out in the middle.

Authors:  H C Guo; T S Jardetzky; T P Garrett; W S Lane; J L Strominger; D C Wiley
Journal:  Nature       Date:  1992-11-26       Impact factor: 49.962

Review 2.  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

3.  Structural prediction of peptides binding to MHC class I molecules.

Authors:  Huynh-Hoa Bui; Alexandra J Schiewe; Hermann von Grafenstein; Ian S Haworth
Journal:  Proteins       Date:  2006-04-01

4.  Efficient peptide-MHC-I binding prediction for alleles with few known binders.

Authors:  Laurent Jacob; Jean-Philippe Vert
Journal:  Bioinformatics       Date:  2007-12-14       Impact factor: 6.937

Review 5.  Positive and negative selection of the alpha beta T-cell repertoire in vivo.

Authors:  H von Boehmer
Journal:  Curr Opin Immunol       Date:  1991-04       Impact factor: 7.486

6.  A flexible docking approach for prediction of T cell receptor-peptide-MHC complexes.

Authors:  Brian G Pierce; Zhiping Weng
Journal:  Protein Sci       Date:  2013-01       Impact factor: 6.725

7.  Analysis of HLA-A24-restricted peptides of carcinoembryonic antigen using a novel structure-based peptide-HLA docking algorithm.

Authors:  Yoji Nakamura; Sachiko Tai; Chie Oshita; Akira Iizuka; Tadashi Ashizawa; Shuji Saito; Shigeki Yamaguchi; Haruhiko Kondo; Ken Yamaguchi; Yasuto Akiyama
Journal:  Cancer Sci       Date:  2011-02-20       Impact factor: 6.716

8.  Cross-allele cytotoxic T lymphocyte responses against 2009 pandemic H1N1 influenza A virus among HLA-A24 and HLA-A3 supertype-positive individuals.

Authors:  Jun Liu; Shihong Zhang; Shuguang Tan; Yong Yi; Bin Wu; Bin Cao; Fengcai Zhu; Chen Wang; Hua Wang; Jianxun Qi; George F Gao
Journal:  J Virol       Date:  2012-09-26       Impact factor: 5.103

9.  Sequence variability analysis of human class I and class II MHC molecules: functional and structural correlates of amino acid polymorphisms.

Authors:  Pedro A Reche; Ellis L Reinherz
Journal:  J Mol Biol       Date:  2003-08-15       Impact factor: 5.469

10.  A novel MHCp binding prediction model.

Authors:  Bing Zhao; Venkatarajan Subramanian Mathura; Ganapathy Rajaseger; Shabbir Moochhala; Meena Kishore Sakharkar; Pandjassarame Kangueane
Journal:  Hum Immunol       Date:  2003-12       Impact factor: 2.850

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  1 in total

1.  General Prediction of Peptide-MHC Binding Modes Using Incremental Docking: A Proof of Concept.

Authors:  Dinler A Antunes; Didier Devaurs; Mark Moll; Gregory Lizée; Lydia E Kavraki
Journal:  Sci Rep       Date:  2018-03-12       Impact factor: 4.379

  1 in total

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