• DocumentCode
    8353
  • Title

    Analysis and classification of DNA-binding sites in single-stranded and double-stranded DNA-binding proteins using protein information

  • Author

    Wei Wang ; Juan Liu ; Yi Xiong ; Lida Zhu ; Xionghui Zhou

  • Author_Institution
    Sch. of Comput., Wuhan Univ., Wuhan, China
  • Volume
    8
  • Issue
    4
  • fYear
    2014
  • fDate
    8 2014
  • Firstpage
    176
  • Lastpage
    183
  • Abstract
    Single-stranded DNA-binding proteins (SSBs) and double-stranded DNA-binding proteins (DSBs) play different roles in biological processes when they bind to single-stranded DNA (ssDNA) or double-stranded DNA (dsDNA). However, the underlying binding mechanisms of SSBs and DSBs have not yet been fully understood. Here, the authors firstly constructed two groups of ssDNA and dsDNA specific binding sites from two non-redundant sets of SSBs and DSBs. They further analysed the relationship between the two classes of binding sites and a newly proposed set of features (residue charge distribution, secondary structure and spatial shape). To assess and utilise the predictive power of these features, they trained a classification model using support vector machine to make predictions about the ssDNA and the dsDNA binding sites. The author´s analysis and prediction results indicated that the two classes of binding sites can be distinguishable by the three types of features, and the final classifier using all the features achieved satisfactory performance. In conclusion, the proposed features will deepen their understanding of the specificity of proteins which bind to ssDNA or dsDNA.
  • Keywords
    DNA; biology computing; molecular biophysics; molecular configurations; pattern classification; proteins; support vector machines; binding mechanisms; biological process; classiflcation model; double-stranded DNA-binding proteins; dsDNA binding sites; protein information; residue charge distribution; secondary structure; single-stranded DNA-binding proteins; spatial shape; ssDNA binding sites; support vector machine;
  • fLanguage
    English
  • Journal_Title
    Systems Biology, IET
  • Publisher
    iet
  • ISSN
    1751-8849
  • Type

    jour

  • DOI
    10.1049/iet-syb.2013.0048
  • Filename
    6869323