• DocumentCode
    772771
  • Title

    Identification of Hot-Spot Locations in Proteins Using Digital Filters

  • Author

    Ramachandran, Parameswaran ; Antoniou, Andreas

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Victoria Univ., Victoria, BC
  • Volume
    2
  • Issue
    3
  • fYear
    2008
  • fDate
    6/1/2008 12:00:00 AM
  • Firstpage
    378
  • Lastpage
    389
  • Abstract
    A technique for the identification of hot-spot locations in proteins using digital filters is described. In this technique, the characteristic frequency of the protein sequence of interest is first determined from the consensus spectrum of the corresponding functional group. The sequence is then filtered by using a specialized narrowband bandpass digital filter in order to select the characteristic frequency. The energy of the filtered output reveals the hot-spot locations. Zero-phase filtering is used to eliminate the need of computing the phase response of the digital filter. The technique has a unique advantage over existing computational hot-spot location techniques in that it identifies the hot-spot locations solely from the amino-acid sequence of a protein, which is usually the only information initially available for a newly discovered protein molecule. This paper deals also with a MATLAB implementation of the technique that incorporates a user-friendly graphical interface. The technique is illustrated using several protein examples and the results obtained are compared with corresponding results based on biological methodologies in order to demonstrate the usefulness, accuracy, and reliability of the technique.
  • Keywords
    filtering theory; graphical user interfaces; medical signal processing; proteins; amino-acid sequence; biological methodologies; digital filters; protein molecule; protein sequence; proteins hot-spot locations; user-friendly graphical interface; zero-phase filtering; Amino acids; Band pass filters; Biochemistry; Biological information theory; Digital filters; Frequency; Genetic mutations; Organisms; Protein engineering; Sequences; Characteristic frequency; consensus spectrum; digital filters; electron-ion interaction potential (EIIP); fast Fourier transform (FFT); hot spots; proteins; resonant recognition model (RRM);
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Signal Processing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1932-4553
  • Type

    jour

  • DOI
    10.1109/JSTSP.2008.923850
  • Filename
    4550565