Reliability of Inhibition Models to Correctly Identify Type of Inhibition
Reliability of Inhibition Models to Correctly Identify Type of Inhibition
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DOI：
10.1007/s11095-010-0236-1
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发表时间：
2010-11-01
影响因子：
3.7
通讯作者：
Polli, James E.
中科院分区：
文献类型：
--
作者：
Kolhatkar, Vidula;Polli, James E.
抑制类型（例如竞争性、非竞争性）经常被评估以了解转运蛋白结构/功能关系，但尚未评估非线性回归正确识别抑制类型的可靠性。其目的是评估非线性回归的能力，正确识别抑制type.This目的是追求通过三个目标，比较竞争性，非竞争性和非竞争性抑制模型，以最佳拟合模拟竞争性和非竞争性数据。第一个目标涉及传统的抑制数据，并涉及模拟数据的常见情况下，底物浓度固定在一个单一的水平，但抑制剂浓度变化。第二个目标涉及Dixon型数据，其中底物和抑制剂浓度均不同。第三个目标涉及非常规抑制数据，其中底物浓度不同，抑制剂固定在单一浓度。实验数据也进行了检查。非线性回归表现不佳，在确定正确的抑制模型，为传统的抑制数据，但表现适度良好的迪克森型数据。有趣的是，非线性回归表现良好的非常规抑制数据，特别是在较高的抑制剂浓度。实验数据支持模拟结果。传统的抑制数据是一个穷人的基础上，以确定抑制类型，而迪克森型数据提供适度的成功。非常规抑制数据值得进一步考虑。
Type of inhibition (e.g. competitive, noncompetitive) is frequently evaluated to understand transporter structure/function relationships, but reliability of nonlinear regression to correctly identify inhibition type has not been assessed. The purpose was to assess the ability of nonlinear regression to correctly identify inhibition type.This aim was pursued through three objectives that compared the competitive, noncompetitive, and uncompetitive inhibition models to best fit simulated competitive and noncompetitive data. The first objective involved conventional inhibition data and entailed simulated data for the common situation where substrate concentration was fixed at a single level but inhibitor concentration varied. The second objective involved Dixon-type data where both substrate and inhibitor concentrations varied. A third objective involved nonconventional inhibition data, where substrate concentration was varied and inhibitor was fixed at a single concentration. Experimental data were also examined.Nonlinear regression performed poorly in identifying the correct inhibition model for conventional inhibition data, but performed moderately well for Dixon-type data. Interestingly, nonlinear regression performed well for nonconventional inhibition data, particularly at higher inhibitor concentrations. Experimental data support simulation findings.Conventional inhibition data is a poor basis to determine inhibition type, while Dixon-type data affords modest success. Nonconventional inhibition data merits further consideration.