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Related Experiment Videos

Octanol-water partition: searching for predictive models

P Buchwald1, N Bodor

  • 1Center for Drug Discovery, University of Florida, Health Science Center, P.O. Box 100497, Gainesville, Florida 32610-0497, USA.

Current Medicinal Chemistry
|October 3, 1998
PubMed
Summary
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Predicting the log n-octanol/water partition coefficient (log Po/w) is crucial for medicinal chemists. This study reviews over 40 methods, highlighting molecular size and hydrogen bonding as key predictors for drug permeability.

Area of Science:

  • Medicinal Chemistry
  • Computational Chemistry
  • Pharmacokinetics

Background:

  • The log n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter in drug discovery.
  • Accurate prediction of log Po/w aids in understanding drug distribution and permeability.
  • Existing prediction models vary in complexity and accuracy.

Purpose of the Study:

  • To review and categorize diverse methods for predicting log Po/w based on molecular structure.
  • To reevaluate the correlation between log Po/w and in vivo brain capillary permeability.
  • To assess the predictive power of molecular size and 3D structure in log Po/w estimation.

Main Methods:

  • Literature review of over 40 log Po/w prediction approaches.
  • Categorization into group contribution, atomic contribution, molecular, and physicochemical methods.

Related Experiment Videos

  • Correlation analysis of log Po/w with rat brain capillary permeability data.
  • Evaluation of a molecular size-based, 3D approach.

    • Main Results:

    • Over 40 prediction methods for log Po/w are presented and categorized.
    • A strong correlation between log Po/w and brain capillary permeability is confirmed, with P-glycoprotein substrates as notable outliers.
    • Molecular size and hydrogen bonding significantly explain log Po/w variance.
    • A 3D molecular size-based approach shows competitive predictive accuracy without empirical fragment constants.

    Conclusions:

    • Log Po/w prediction remains vital for medicinal chemistry, with diverse computational methods available.
    • Understanding factors like P-glycoprotein efflux is crucial for interpreting permeability data.
    • Molecular size and 3D structural features offer promising avenues for accurate and simplified log Po/w prediction.