Dissecting the statistical properties of the linear extrapolation method of determining protein stability.

IF 2.6 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Protein Engineering Design & Selection Pub Date : 2019-12-31 DOI:10.1093/protein/gzaa010
Kresten Lindorff-Larsen
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引用次数: 5

Abstract

The linear extrapolation method to determine protein stability from denaturant-induced unfolding experiments is based on the observation that the free energy of unfolding is often a linear function of the denaturant concentration. The value in the absence of denaturant is then estimated by extrapolation from this linear relationship. Parameters and their confidence intervals are typically estimated by nonlinear least-squares regression. We have compared different methods for calculating confidence intervals and found that a simple method based on linear theory gives accurate results. We have also compared three different parameterizations of the linear extrapolation method and show that the most commonly used form is problematic since the stability and m-value are correlated in the nonlinear least-squares analysis. Parameter correlation can in some cases causes problems in the estimation of confidence intervals and regions and should be avoided when possible. Two alternative parameterizations show much less correlation between parameters.

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剖析了测定蛋白质稳定性的线性外推法的统计特性。
从变性剂诱导的展开实验中确定蛋白质稳定性的线性外推法是基于这样的观察,即展开的自由能通常是变性剂浓度的线性函数。在没有变性剂的情况下,通过从这种线性关系外推来估计值。参数及其置信区间一般采用非线性最小二乘回归估计。我们比较了计算置信区间的不同方法,发现一种基于线性理论的简单方法可以得到准确的结果。我们还比较了线性外推方法的三种不同的参数化,并表明最常用的形式是有问题的,因为在非线性最小二乘分析中稳定性和m值是相关的。参数相关性在某些情况下会导致估计置信区间和区域的问题,应该尽可能避免。两种可选的参数化显示参数之间的相关性要小得多。
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来源期刊
Protein Engineering Design & Selection
Protein Engineering Design & Selection 生物-生化与分子生物学
CiteScore
3.30
自引率
4.20%
发文量
14
审稿时长
6-12 weeks
期刊介绍: Protein Engineering, Design and Selection (PEDS) publishes high-quality research papers and review articles relevant to the engineering, design and selection of proteins for use in biotechnology and therapy, and for understanding the fundamental link between protein sequence, structure, dynamics, function, and evolution.
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