• DocumentCode
    78617
  • Title

    Quantifying Significance of MHC II Residues

  • Author

    Ying Fan ; Ruoshui Lu ; Lusheng Wang ; Andreatta, Massimo ; Shuai Cheng Li

  • Author_Institution
    Dept. of Comput. Sci., City Univ. of Hong Kong, Kowloon, China
  • Volume
    11
  • Issue
    1
  • fYear
    2014
  • fDate
    Jan.-Feb. 2014
  • Firstpage
    17
  • Lastpage
    25
  • Abstract
    The major histocompatibility complex (MHC), a cell-surface protein mediating immune recognition, plays important roles in the immune response system of all higher vertebrates. MHC molecules are highly polymorphic and they are grouped into serotypes according to the specificity of the response. It is a common belief that a protein sequence determines its three dimensional structure and function. Hence, the protein sequence determines the serotype. Residues play different levels of importance. In this paper, we quantify the residue significance with the available serotype information. Knowing the significance of the residues will deepen our understanding of the MHC molecules and yield us a concise representation of the molecules. In this paper we propose a linear programming-based approach to find significant residue positions as well as quantifying their significance in MHC II DR molecules. Among all the residues in MHC II DR molecules, 18 positions are of particular significance, which is consistent with the literature on MHC binding sites, and succinct pseudo-sequences appear to be adequate to capture the whole sequence features. When the result is used for classification of MHC molecules with serotype assigned by WHO, a 98.4 percent prediction performance is achieved. The methods have been implemented in java (http://code.google.com/p/quassi/).
  • Keywords
    biochemistry; cellular biophysics; linear programming; molecular biophysics; proteins; MHC II DR molecules; MHC II residues; MHC binding sites; MHC molecules; cell-surface protein mediating immune recognition; high polymorphism; high vertebrates; immune response system; linear programming-based approach; major histocompatibility complex; molecule representation; prediction performance; protein sequence; residue positions; serotype information; serotypes; succinct pseudosequences; three dimensional structure; whole sequence features; Amino acids; Bioinformatics; Immune system; Integer linear programming; Mathematical model; Peptides; Vectors; MHC II molecules; integer linear programming; quantify significant residues (positions);
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2013.138
  • Filename
    6654172