Assessment of n-octanol/water partition coefficient: when is the assessment reliable?
A model, VLOGP, has been developed for assessment of n-octanol/water partition coefficient, log P, of chemicals from their structures. Unlike group contribution methods, VLOGP is based on linear free energy relationship (LFER) approach and employs information-rich electrotopological structure quantifiers derived solely from molecular topology. VLOGP, a robust and cross-validated model derived from accurately measured experimental log P values of 6675 diverse chemicals, has a coefficient of determination, R2, of 0.986 and a standard error of estimate of 0.20. When applied to the training set, the largest deviation observed between experimental and calculated log P was 0.42. VLOGP is different from other log P predictors in that its application domain, called Optimum Prediction Space (OPS), has been quantitatively defined, i.e., structures to which the model should not be applied for predicting log P can be identified. A computer-assisted implementation of this model within HDi's toxicity assessment software package, TOPKAT 3.0, automatically checks whether the submitted structure is inside the OPS or not. VLOGP was applied to a set of 113 chemicals not included in the training set. It was observed that for the structures inside the OPS the average deviation between experimental and model-calculated log P values is 0.27, whereas the corresponding deviation for structures outside the OPS is 1.35. This demonstrates the necessity of identifying the structures to which a model is not applicable before accepting a model-based predicted log P value. For a set of 47 nucleosides, the performance of VLOGP was compared with that of four published log P predictors; a standard deviation of 0.33 was obtained with VLOGP, whereas the standard deviation from other log P predictors ranged between 0.46 and 1.20.
Gombar
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VK
Health Designs, Inc., Rochester, New York 14604, USA.
Enslein
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D020003:1-Octanol; D000465:Algorithms; D001692:Biological Transport; D003198:Computer Simulation; D008566:Membranes / Q000378:metabolism; D008954:Models, Biological; D015394:Molecular Structure; D000442:Octanols; D014867:Water
D000442:Octanols; D014867:Water; D020003:1-Octanol