首页> 外文期刊>Methods: A Companion to Methods in Enzymology >High-precision, automated integration of multiple isothermal titration calorimetric thermograms: New features of NITPIC
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High-precision, automated integration of multiple isothermal titration calorimetric thermograms: New features of NITPIC

机译:多个等温滴定热分析图的高精度,自动化集成:NITPIC的新功能

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Isothermal titration calorimetry (ITC) has become a standard and widely available tool to measure the thermodynamic parameters of macromolecular associations. Modern applications of the method, including global analysis and drug screening, require the acquisition of multiple sets of data; sometimes these data sets number in the hundreds. Therefore, there is a need for quick, precise, and automated means to process the data, particularly at the first step of data analysis, which is commonly the integration of the raw data to yield an interpretable isotherm. Herein, we describe enhancements to an algorithm that previously has been shown to provide an automated, unbiased, and high-precision means to integrate ITC data. These improvements allow for the speedy and precise serial integration of an unlimited number of ITC data sets, and they have been implemented in the freeware program NITPIC, version 1.1.0. We present a comprehensive comparison of the performance of this software against an older version of NITPIC and a current version of Origin, which is commonly used for integration. The new methods recapitulate the excellent performance of the previous versions of NITPIC while speeding it up substantially, and their precision is significantly better than that of Origin. This new version of NITPIC is therefore well suited to the serial integration of many ITC data sets. (C) 2014 Elsevier Inc. All rights reserved.
机译:等温滴定热量法(ITC)已成为测量大分子缔合的热力学参数的标准且广泛使用的工具。该方法的现代应用,包括全局分析和药物筛选,需要获取多组数据;有时这些数据集有数百个。因此,需要一种快速,精确和自动化的方式来处理数据,尤其是在数据分析的第一步,这通常是原始数据的集成以产生可解释的等温线。本文中,我们描述了一种算法的增强功​​能,该算法先前已被证明可以提供自动,无偏且高精度的方法来集成ITC数据。这些改进允许对无限数量的ITC数据集进行快速,精确的串行集成,并且已在免费软件程序NITPIC 1.1.0版中实现了这些改进。我们提供了此软件与较旧版本的NITPIC和当前用于集成的Origin的当前版本的综合比较。新方法概括了以前版本的NITPIC的出色性能,同时大大提高了它的精度,其精度明显优于Origin。因此,此新版本的NITPIC非常适合于许多ITC数据集的串行集成。 (C)2014 Elsevier Inc.保留所有权利。

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