4.7 Article

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

期刊

MOLECULAR PHARMACEUTICS
卷 11, 期 8, 页码 2962-+

出版社

AMER CHEMICAL SOC
DOI: 10.1021/mp500103r

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

资金

  1. European Commission through a Marie Curie Intra-European Fellowship - European Community
  2. University of Strathclyde
  3. EPSRC
  4. EPSRC [EP K0005861]
  5. Scottish Universities Life Sciences Alliance (SULSA)
  6. EPSRC [EP/K000195/1] Funding Source: UKRI
  7. Engineering and Physical Sciences Research Council [EP/K000195/1] Funding Source: researchfish

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据