Is Experimental Data Quality the Limiting Factor in Predicting the Aqueous Solubility of Druglike Molecules?

被引:99
作者
Palmer, David S. [1 ]
Mitchell, John B. O. [2 ,3 ]
机构
[1] Univ Strathclyde, Dept Chem, Glasgow G1 1XL, Lanark, Scotland
[2] Univ St Andrews, St Andrews KY16 9ST, Fife, Scotland
[3] Univ St Andrews, EaStCHEM Sch Chem, St Andrews KY16 9ST, Fife, Scotland
基金
英国工程与自然科学研究理事会;
关键词
solubility; bioavailability; QSPR; QSAR; druglike; ADME; Random Forest; dissolution; experimental error; CheqSol; Noyes-Whitney; Henderson-Hasselbalch; polymorph; crystal; machine learning; general solubility equation; ADMET; pharmaceutical; rule-of-five; ORGANIC-COMPOUNDS; MELTING-POINT; RANDOM FOREST; EQUATION GSE; MODELS; THERMODYNAMICS; DISCOVERY; PERMEABILITY; CHALLENGE; COMPOUND;
D O I
10.1021/mp500103r
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
We report the results of testing quantitative structure property relationships (QSPR) that were trained upon the same druglike molecules but two different sets of solubility data: (i) data extracted from several different sources from the published literature, for which the experimental uncertainty is estimated to be 0.6-0.7 log S units (referred to mol/L); (ii) data measured by a single accurate experimental method (CheqSol), for which experimental uncertainty is typically <0.05 log S units. Contrary to what might be expected, the models derived from the CheqSol experimental data are not more accurate than those derived from the "noisy" literature data. The results suggest that, at the present time, it is the deficiency of QSPR methods (algorithms and/or descriptor sets), and not, as is commonly quoted, the uncertainty in the experimental measurements, which is the limiting factor in accurately predicting aqueous solubility for pharmaceutical molecules.
引用
收藏
页码:2962 / +
页数:11
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