Gubler Hanspeter, Schopfer Ulrich, Jacoby Edgar
Informatics and Technology, Novartis Pharma AG, Institutes for BioMedical Research, Basel, Switzerland.
J Biomol Screen. 2013 Jan;18(1):1-13. doi: 10.1177/1087057112455219. Epub 2012 Aug 1.
The four-parameter logistic Hill equation models the theoretical relationship between inhibitor concentration and response and is used to derive IC(50) values as a measure of compound potency. This relationship is the basis for screening strategies that first measure percent inhibition at a single, uniform concentration and then determine IC(50) values for compounds above a threshold. In screening practice, however, a "good" correlation between percent inhibition values and IC(50) values is not always observed, and in the literature, there seems confusion about what correlation even to expect. We examined the relationship between percent inhibition data and IC(50) data in HDAC4 and ENPP2 high-throughput screening (HTS) data sets and compared our findings with a series of numerical simulations that allowed the investigation of the influence of parameters representing different types of uncertainties: variability in the screening concentration (related to solution library and compound characteristics, liquid handling), variations in Hill model parameters (related to interaction of compounds with target, type of assay), and influences of assay data quality parameters (related to assay and experimental design, liquid handling). In the different sensitivity analyses, we found that the typical variations of the actual compound concentrations in existing screening libraries generate the largest contributions to imperfect correlations. Excess variability in the ENPP2 assay above the values of the simulation model can be explained by compound aggregation artifacts.
四参数逻辑斯蒂希尔方程对抑制剂浓度与反应之间的理论关系进行建模,并用于推导IC(50)值,作为化合物效力的一种度量。这种关系是筛选策略的基础,该策略首先在单一、统一的浓度下测量抑制百分比,然后确定高于阈值的化合物的IC(50)值。然而,在筛选实践中,抑制百分比值与IC(50)值之间并不总是能观察到“良好”的相关性,而且在文献中,对于预期的相关性似乎也存在混淆。我们研究了HDAC4和ENPP2高通量筛选(HTS)数据集中抑制百分比数据与IC(50)数据之间的关系,并将我们的发现与一系列数值模拟进行了比较,这些模拟允许研究代表不同类型不确定性的参数的影响:筛选浓度的变异性(与溶液文库和化合物特性、液体处理有关)、希尔模型参数的变化(与化合物与靶点的相互作用、测定类型有关)以及测定数据质量参数的影响(与测定和实验设计、液体处理有关)。在不同的敏感性分析中,我们发现现有筛选文库中实际化合物浓度的典型变化对不完美相关性的贡献最大。ENPP2测定中高于模拟模型值的过度变异性可以用化合物聚集假象来解释。