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Binding Isotherms and Time Courses Readily from MagneticResonance

机译:轻松绑定磁性等温线和时程谐振

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摘要

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 obviatesthe customary focus on specific peaks or regions of images. Applyingit directly to a series of complex data will easily delineate bindingisotherms, equilibrium shifts, and time courses of reactions or fluctuations.
机译:证据表明,可以使用主成分分析(PCA)从未解释的复杂2D NMR光谱中直接提取简单或双相的结合等温线,以揭示整个系列的最大趋势。这种方法使峰值选择对于跟踪总体变化而言是不必要的。在1:1结合中,第一个主要成分以快速,缓慢甚至中间和混合交换方式从NMR检测的滴定中捕获结合等温线,如磷酸配体与蛋白质的结合所示。尽管中间交换的S形偏移和线展宽扭曲了按常规方式构造的结合等温线,但将PCA直接应用于这些光谱以及Pareto缩放比例可以克服这种扭曲。将PCA应用于时域NMR数据还可以通过快速或缓慢交换中的滴定产生结合等温线。该算法很容易从磁共振成像中提取电影时间过程,例如胸部成像中的呼吸和心率。同样,通过NMR检测的两步结合过程很容易被主要成分1和2捕获。PCA消除了通常将重点放在图像的特定峰或区域。正在申请直接将其复制到一系列复杂数据中,将很容易划定绑定等温线,平衡位移以及反应或波动的时间过程。

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