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Confidence interval estimators for parameters associated with quantitative structure-activity relationships

S W Dietrich, N D Dreyer, C Hansch

    Journal of Medicinal Chemistry
    |November 1, 1980
    PubMed
    Summary
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    The jackknife statistical method provides reliable point and confidence interval estimators for complex model parameters. This approach is useful for quantitative structure-activity relationship (QSAR) models and enzyme inhibition studies.

    Area of Science:

    • Statistics
    • Computational Chemistry
    • Biochemistry

    Background:

    • Regression coefficients and iteratively estimated parameters are crucial in various modeling techniques.
    • Quantitative Structure-Activity Relationship (QSAR) models describe the relationship between chemical structures and biological activity.
    • Enzyme inhibition kinetics are fundamental in drug discovery and biochemical research.

    Purpose of the Study:

    • To describe the application of the jackknife method for constructing statistical estimators.
    • To demonstrate the utility of the jackknife for parameters derived from regression and iterative estimations.
    • To showcase its use in QSAR and enzyme inhibition contexts.

    Main Methods:

    • The jackknife, a resampling technique, was employed for statistical estimation.

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  • Point and confidence interval estimators were constructed for parameters that are functions of regression coefficients.
  • The method was applied to parameters from parabolic and bilinear QSAR models and competitive enzyme inhibition models.

    • Main Results:

    • The jackknife successfully generated reliable point and confidence interval estimators.
    • Its effectiveness was demonstrated for parameters like log P0 and pi 0 in QSAR.
    • The method proved useful for estimating log [1/Ki(app)] in competitive enzyme inhibition.

    Conclusions:

    • The jackknife is a versatile statistical tool for parameter estimation in complex models.
    • It enhances the reliability of estimators in QSAR and enzyme kinetics.
    • This method offers a robust approach for constructing confidence intervals for derived parameters.