Molecular Biophysics, University of Kaiserslautern, 67663 Kaiserslautern, Germany.
Anal Chem. 2012 Jun 5;84(11):5066-73. doi: 10.1021/ac3007522. Epub 2012 May 14.
Isothermal titration calorimetry (ITC) is a powerful classical method that enables researchers in many fields to study the thermodynamics of molecular interactions. Primary ITC data comprise the temporal evolution of differential power reporting the heat of reaction during a series of injections of aliquots of a reactant into a sample cell. By integration of each injection peak, an isotherm can be constructed of total changes in enthalpy as a function of changes in solution composition, which is rich in thermodynamic information on the reaction. However, the signals from the injection peaks are superimposed by the stochastically varying time-course of the instrumental baseline power, limiting the precision of ITC isotherms. Here, we describe a method for automated peak assignment based on peak-shape analysis via singular value decomposition in combination with detailed least-squares modeling of local pre- and postinjection baselines. This approach can effectively filter out contributions of short-term noise and adventitious events in the power trace. This method also provides, for the first time, statistical error estimates for the individual isotherm data points. In turn, this results in improved detection limits for high-affinity or low-enthalpy binding reactions and significantly higher precision of the derived thermodynamic parameters.
等温滴定量热法(ITC)是一种强大的经典方法,使许多领域的研究人员能够研究分子相互作用的热力学。主要的 ITC 数据包括报告一系列反应物等分注入样品池过程中反应热的差示功率的时间演化。通过对每个注入峰的积分,可以构建焓的总变化作为溶液组成变化的函数的等温线,其中包含有关反应的丰富热力学信息。然而,注入峰的信号被仪器基线功率的随机时变过程所叠加,从而限制了 ITC 等温线的精度。在这里,我们描述了一种基于通过奇异值分解进行峰形分析的自动峰分配方法,以及对局部预注入和后注入基线的详细最小二乘建模。该方法可以有效地滤除功率迹线中短期噪声和偶然事件的贡献。该方法还首次为单个等温线数据点提供了统计误差估计。反过来,这提高了高亲和力或低焓结合反应的检测限,并显著提高了推导热力学参数的精度。