• DocumentCode
    1791827
  • Title

    A novel approach to determine docking locations using fuzzy logic and shape determination

  • Author

    Umoja, Chinua ; Torrance, J.T. ; Durham, Erin-Elizabeth A. ; Rosen, Arye ; Harrison, Robert W.

  • Author_Institution
    Comput. Sci. Dept., Georgia State Univ., Atlanta, GA, USA
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    14
  • Lastpage
    16
  • Abstract
    The determination of whether a molecule can bind or ”dock” a protein to a certain site depends on the orientation of the molecules, the charge of the atoms that comprise the molecules, and the electrical potential of the proposed area. It is said that a fundamental problem with molecular docking is that the orientation space itself is very large and grows in a combinatorial manner with the number of degrees of freedom of the interacting molecules. We tried to cleverly solve this problem by using shape definitions and fuzzy logic to help reduce the search size of possible docking locations and predict which locations and orientations are the most likely docking locations.
  • Keywords
    biology computing; fuzzy logic; proteins; proteomics; atoms; docking locations; fuzzy logic; molecule; protein; shape determination; Atomic measurements; Databases; Electric potential; Mathematical model; Probes; Proteins; Shape; Computational Prediction; Computational Probability and Analysis; Data Mining; Fuzzy Decisioning; Molecular Binding; Molecular Protein Docking Algorithm; Relational Database;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (Big Data), 2014 IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Type

    conf

  • DOI
    10.1109/BigData.2014.7004478
  • Filename
    7004478