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热荧光数据等温分析可以方便地提供定量结合亲和力。

Isothermal Analysis of ThermoFluor Data can readily provide Quantitative Binding Affinities.

机构信息

Program in Molecular Therapeutics, Fox Chase Cancer Center, Philadelphia, PA, 19111, USA.

Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66045, USA.

出版信息

Sci Rep. 2019 Feb 25;9(1):2650. doi: 10.1038/s41598-018-37072-x.

Abstract

Differential scanning fluorimetry (DSF), also known as ThermoFluor or Thermal Shift Assay, has become a commonly-used approach for detecting protein-ligand interactions, particularly in the context of fragment screening. Upon binding to a folded protein, most ligands stabilize the protein; thus, observing an increase in the temperature at which the protein unfolds as a function of ligand concentration can serve as evidence of a direct interaction. While experimental protocols for this assay are well-developed, it is not straightforward to extract binding constants from the resulting data. Because of this, DSF is often used to probe for an interaction, but not to quantify the corresponding binding constant (K). Here, we propose a new approach for analyzing DSF data. Using unfolding curves at varying ligand concentrations, our "isothermal" approach collects from these the fraction of protein that is folded at a single temperature (chosen to be temperature near the unfolding transition). This greatly simplifies the subsequent analysis, because it circumvents the complicating temperature dependence of the binding constant; the resulting constant-temperature system can then be described as a pair of coupled equilibria (protein folding/unfolding and ligand binding/unbinding). The temperature at which the binding constants are determined can also be tuned, by adding chemical denaturants that shift the protein unfolding temperature. We demonstrate the application of this isothermal analysis using experimental data for maltose binding protein binding to maltose, and for two carbonic anhydrase isoforms binding to each of four inhibitors. To facilitate adoption of this new approach, we provide a free and easy-to-use Python program that analyzes thermal unfolding data and implements the isothermal approach described herein ( https://sourceforge.net/projects/dsf-fitting ).

摘要

差示扫描荧光法(DSF),也称为热荧光或热转移分析,已成为检测蛋白-配体相互作用的常用方法,尤其是在片段筛选的背景下。大多数配体与折叠的蛋白质结合后会稳定蛋白质;因此,观察到蛋白质在配体浓度的函数下展开的温度增加,可以作为直接相互作用的证据。虽然该测定的实验方案已经很成熟,但从得到的数据中提取结合常数并不简单。正因为如此,DSF 通常用于探测相互作用,但不能定量相应的结合常数(K)。在这里,我们提出了一种分析 DSF 数据的新方法。使用不同配体浓度下的展开曲线,我们的“等温”方法从这些曲线上收集在单个温度下折叠的蛋白质分数(选择接近展开转变的温度)。这大大简化了后续分析,因为它避免了结合常数的复杂温度依赖性;由此产生的恒温水系统可以描述为一对偶联平衡(蛋白质折叠/展开和配体结合/解吸)。通过添加化学变性剂来改变蛋白质展开温度,也可以调整确定结合常数的温度。我们使用麦芽糖结合蛋白与麦芽糖结合以及两种碳酸酐酶同工型与四种抑制剂中的每一种结合的实验数据来演示这种等温分析的应用。为了方便采用这种新方法,我们提供了一个免费且易于使用的 Python 程序,该程序可分析热展开数据并实现本文所述的等温方法(https://sourceforge.net/projects/dsf-fitting)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e6e/6389909/a978a440b9a2/41598_2018_37072_Fig1_HTML.jpg

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