• Title of article

    Experimental determination and prediction of bilitranslocase transport activity Original Research Article

  • Author/Authors

    Spela Zuperl، نويسنده , , Stefano Fornasaro، نويسنده , , Marjana Novic، نويسنده , , Sabina Passamonti، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2011
  • Pages
    12
  • From page
    322
  • To page
    333
  • Abstract
    The transport activity of a membrane protein, bilitranslocase (T.C. # 2.A.65.1.1), which acts as a transporter of bilirubin from blood to liver cells, was experimentally determined for a large set of various endogenous compounds, drugs, purine and pyrimidine derivatives. On these grounds, the structure–activity models were developed following the OECD principles of QSAR models and their predictive ability for new chemicals was evaluated. The applicability domain of the models was estimated by Euclidean distances criteria according to the applied modeling method. The selection of the most influential structural variables was an important stage in the adopted modeling methodology. The interpretation of selected variables was performed in order to get an insight into the mechanism of transport through the cell membrane via bilitranslocase. Validation of the optimized models was performed by a previously determined validation set. The classification model was build to separate active from inactive compounds. The resulting accuracy, sensitivity, and specificity were 0.73, 0.89, and 0.64, respectively. Only active compounds were used to develop a predictive model for bilitranslocase inhibition constants. The model showed good predictive ability; Root Mean Squared error of the validation set, RMSV = 0.29 log units.
  • Keywords
    Drug target , Inhibition constants , classification , Artificial neural network , Predictive models , variable selection , Applicability domain , Bilitranslocase transport activity
  • Journal title
    Analytica Chimica Acta
  • Serial Year
    2011
  • Journal title
    Analytica Chimica Acta
  • Record number

    1026723