Research ArticlesPrediction of the aqueous solubility: Comparison of the general solubility equation and the method using an amended solvation energy relationship
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INTRODUCTION
Aqueous solubility is a crucial physical property in pharmaceutical and environmental research. Several methods for the prediction of the aqueous solubility have been published in recent years.1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11., 12., 13. The General Solubility Equation (GSE), as initially proposed by Yalkowsky and Valvani in 1980,2 and recently revised by Jain and Yalkowsky,13 has been used widely. The GSE relates the molar aqueous solubility (Sw) to the Celsius melting point (mp) and
METHODS
The melting point data for the 664 compounds were obtained from the AQUASOL dATAbASE, Merck Index, and several Internet databases. The octanol–water partition coefficients were calculated with CLOGP® software (Version 4.0, BioByte Corp., Claremont, CA). Experimental octanol–water partition coefficients are listed if available. The experimental aqueous solubilities and the ASER predicted solubilities are those reported by Abraham and Le.14 The aqueous solubilities were also calculated using the
Octanol–Water Partition Coefficient
Experimental partition coefficients were found for 530 of the 664 compounds. As shown in Figure 1, the calculated partition coefficients using CLOGP® are in very good agreement with the available measured values (MLOGP), with an AAE of only 0.121 log units. CLOGP® version 4.0 seems to give more accurate estimations of octanol–water partition coefficients than the previous version. Partition coefficients calculated with CLOGP® are used in the solubility calculations because they are easily
DISCUSSION
In spite of the fact that the GSE uses only two input variables and does not use any training set or fitted parameters, it gives quite reasonable predictions. The ASER method produces only marginally better predictions (Table 1). However, the ASER method uses seven coefficients, six variables derived from a very large number of structural descriptor values, and multiple linear regression analysis.
As can be seen in Table 1, both methods give better prediction for the 408 liquids than for the 256
CONCLUSIONS
Both the ASER and the GSE methods give satisfactory prediction for the compound set. The ASER is based on multiple linear regression analysis of a large training set that may or may not contain the required structural fragments, whereas the GSE is simpler and more user‐friendly. However, the latter requires knowledge of either an experimentally determined or an estimated mp of the solute. This study provides support for the reliability of the GSE in estimating the aqueous solubilities of
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