Department of Analytical Chemistry, GlaxoSmithKline Medicines Research Centre, Stevenage, Hertfordshire SG1 2NY, UK.
Drug Discov Today. 2010 Aug;15(15-16):648-55. doi: 10.1016/j.drudis.2010.05.016. Epub 2010 Jun 4.
Suboptimal physical properties have been identified as a particular shortcoming of compounds in contemporary drug discovery, contributing to high attrition levels. An analysis of the relationship between hydrophobicity (calculated and measured) and approximately 100k measured kinetic solubility values has been undertaken. In line with the General Solubility Equation, estimates of hydrophobicity, particularly ACD clogD(pH7.4), give a useful indication of the likely solubility classification of particular molecules. Taking ACD clogD(pH7.4) values together with the number of aromatic rings in a given molecule provides enhanced prediction. The 'Solubility Forecast Index' (SFI=clogD(pH7.4)+#Ar) is proposed as a simple, yet effective, guide to predicting solubility. Moreover, analysis of measured distribution/partition coefficient values highlighted statistically significant shortcomings in the applicability of octanol/water as a model system for hydrophobicity determination with poorly soluble compounds.
物理性质不理想被认为是当代药物发现中化合物的一个特别缺点,导致高淘汰率。对疏水性(计算和测量)与大约 100k 个测量的动力学溶解度值之间的关系进行了分析。与通用溶解度方程一致,疏水性的估计值,特别是 ACD clogD(pH7.4),对特定分子的可能溶解度分类提供了有用的指示。将 ACD clogD(pH7.4)值与给定分子中的芳环数结合起来,可以提供增强的预测。提出“溶解度预测指数”(SFI=clogD(pH7.4)+#Ar)作为一种简单而有效的方法,用于预测溶解度。此外,对测量的分布/分配系数值的分析突出表明,对于疏水性测定,辛醇/水作为模型系统的适用性存在统计学上的显著缺陷,对于难溶性化合物而言。