Klopman G, Wang S, Balthasar D M
Department of Chemistry, Case Western Reserve University, Cleveland, Ohio 44106-7078.
J Chem Inf Comput Sci. 1992 Sep-Oct;32(5):474-82. doi: 10.1021/ci00009a013.
A reliable and generally applicable aqueous solubility estimation method for organic compounds based on a group contribution approach has been developed. Two models have been established based on two different sets of parameters. One has a higher accuracy, while the other has a more general applicability. The prediction potentials of these two models have been evaluated through cross-validation experiments. For model I, the mean cross-validated r2 and SD for 10 such cross-validation experiments were 0.946 and 0.503 log units, respectively. While for model II, they were 0.953 and 0.546 log units, respectively. Applying our models to estimate the water solubility values for the compounds in an independent test set, we found that model I can be applied to 13 out of 21 compounds with a SD equal to 0.58 log unit and model II can be applied to all the 21 compounds with a SD equal to 1.25 log units. Our models compare favorably to all the current available water estimation methods. A program based on this approach has been written in FORTRAN77 and is currently running on a VAX/VMS system. The program can be applied to estimate the water solubility of the water solubility of any organic chemical with a good or fairly good accuracy except for except for electrolytes. Applying our aqueous solubility estimation models to biodegradation studies, we found that although the water solubility was not the sole factor controlling the rate of biodegradation, ring compounds with greater solubilities were more likely to biodegrade at a faster rate. The significance of the relationship between water solubility and biodegradation activity has been illustrated by predicting the biodegradation activity of 27 new chemicals based solely on their estimated solubility values.
已开发出一种基于基团贡献法的可靠且普遍适用的有机化合物水溶性估算方法。基于两组不同参数建立了两个模型。一个具有较高的准确性,另一个具有更广泛的适用性。通过交叉验证实验评估了这两个模型的预测潜力。对于模型I,10次此类交叉验证实验的平均交叉验证r2和SD分别为0.946和0.503对数单位。而对于模型II,它们分别为0.953和0.546对数单位。将我们的模型应用于独立测试集中化合物的水溶性值估算,我们发现模型I可应用于21种化合物中的13种,SD等于0.58对数单位,模型II可应用于所有21种化合物,SD等于1.25对数单位。我们的模型与所有现有的水溶性估算方法相比具有优势。基于此方法的程序已用FORTRAN77编写,目前正在VAX/VMS系统上运行。该程序可用于估算任何有机化学品的水溶性,除电解质外,准确性良好或相当好。将我们的水溶性估算模型应用于生物降解研究,我们发现尽管水溶性不是控制生物降解速率的唯一因素,但溶解度较大的环状化合物更有可能以更快的速率进行生物降解。通过仅根据其估算的溶解度值预测27种新化学品的生物降解活性,说明了水溶性与生物降解活性之间关系的重要性。