Inclusion of Control Data in Fits to Concentration–Response Curves Improves Estimates of Half-Maximal Concentrations
Inclusion of Control Data in Fits to Concentration–Response Curves Improves Estimates of Half-Maximal Concentrations
复制标题
将控制数据包含在浓度拟合响应曲线中可改进半最大浓度的估计
DOI：
10.1021/acs.jmedchem.3c00107
复制
发表时间：
2023
影响因子：
7.3
通讯作者：
Minh, David D. L.
中科院分区：
文献类型：
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作者：
La, Van Ngoc Thuy;Nicholson, Stanley;Haneef, Amna;Kang, Lulu;Minh, David D. L.
浓度-反应曲线是用来测量不同浓度对检测反应的影响的曲线，被广泛用于评价化合物的生物效应。虽然国家先进翻译科学中心的指南规定读数应该由对照进行标准化，但推荐的统计分析并不明确地适合对照数据。在这里，我们介绍了一种基于最大似然估计的非线性回归方法，该方法通过将模型与曲线和控制数据进行拟合来确定经典Hill方程的参数。仿真结果表明，与以往的方法相比，该方法提供了更精确的参数。对COVID月球拍摄的酶抑制数据的分析表明，所提出的方法产生了较低的估计参数的渐近标准误差。在对不完全曲线的分析中，收益最为明显。我们还发现，朗斯的离群点检测方法似乎能更准确地确定参数。
Concentration–response curves, in which the effect of varying the concentration on the response of an assay is measured, are widely used to evaluate biological effects of chemical compounds. While National Center for Advancing Translational Sciences guidelines specify that readouts should be normalized by the controls, recommended statistical analyses do not explicitly fit to the control data. Here, we introduce a nonlinear regression procedure based on maximum likelihood estimation that determines parameters for the classical Hill equation by fitting the model to both the curve and the control data. Simulations show that the proposed procedure provides more precise parameters compared with previously prescribed practices. Analysis of enzymatic inhibition data from the COVID Moonshot demonstrates that the proposed procedure yields a lower asymptotic standard error for estimated parameters. Benefits are most evident in the analysis of the incomplete curves. We also find that Lenth’s outlier detection method appears to determine parameters more precisely.