Binding Isotherms and Time Courses Readily from Magnetic Resonance.
Binding Isotherms and Time Courses Readily from Magnetic Resonance.
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磁共振容易结合等温线和时间课程。
DOI：
10.1021/acs.analchem.6b01918
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发表时间：
2016-08-16
影响因子：
7.4
通讯作者：
Van Doren SR
中科院分区：
文献类型：
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作者：
Xu J;Van Doren SR
有证据表明，使用主成分分析(PCA)可以直接从未解释的复杂2D核磁共振谱中提取结合等温线，无论是简单的还是两相的，以揭示整个系列的最大趋势(S)。这种方法使得在跟踪种群变化时没有必要进行高峰选择。在1：1结合中，第一主成分从核磁共振检测的滴定中捕获快速、缓慢、甚至中间和混合交换模式的结合等温线，如磷配体与蛋白质的结合。尽管中间交换的S型位移和线宽扭曲了传统构造的结合等温线，但将主成分分析直接应用于这些光谱并结合Pareto标度克服了这种扭曲。将主成分分析应用于时间域核磁共振数据也可以从快速或缓慢交换的滴定中获得结合等温线。该算法很容易从磁共振成像中提取电影时间进程，如胸部成像中的呼吸和心率。同样，核磁共振检测到的两步结合过程很容易被主成分1和2捕获。主成分分析避免了通常集中在图像的特定峰或区域上。将它直接应用于一系列复杂的数据，可以很容易地描绘出结合等温线、平衡位移和反应或波动的时间进程。
Evidence is presented that binding isotherms, simple or biphasic, can be extracted directly from noninterpreted, complex 2D NMR spectra using principal component analysis (PCA) to reveal the largest trend(s) across the series. This approach renders peak picking unnecessary for tracking population changes. In 1:1 binding, the first principal component captures the binding isotherm from NMR-detected titrations in fast, slow, and even intermediate and mixed exchange regimes, as illustrated for phospholigand associations with proteins. Although the sigmoidal shifts and line broadening of intermediate exchange distorts binding isotherms constructed conventionally, applying PCA directly to these spectra along with Pareto scaling overcomes the distortion. Applying PCA to time-domain NMR data also yields binding isotherms from titrations in fast or slow exchange. The algorithm readily extracts from magnetic resonance imaging movie time courses such as breathing and heart rate in chest imaging. Similarly, two-step binding processes detected by NMR are easily captured by principal components 1 and 2. PCA obviates the customary focus on specific peaks or regions of images. Applying it directly to a series of complex data will easily delineate binding isotherms, equilibrium shifts, and time courses of reactions or fluctuations.