Practical model fitting approaches to the direct extraction of NMR parameters simultaneously from all dimensions of multidimensional NMR spectra
Practical model fitting approaches to the direct extraction of NMR parameters simultaneously from all dimensions of multidimensional NMR spectra
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DOI：
10.1023/a:1008254432254
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发表时间：
1998-08-01
影响因子：
2.7
通讯作者：
Markley, JL
中科院分区：
文献类型：
--
作者：
Chylla, RA;Volkman, BF;Markley, JL
建立了一种基于最大似然(ML)的方法，用于从D-维核磁共振谱的所有维度同时直接提取核磁共振参数(例如，频率、幅度、相位和衰减率)。这种方法，这里称为HTFD-ML(混合时频域最大似然)，构造了由指数衰减的正弦信号之和组成的时域模型。该时间域信号的变迹傅里叶变换是代表与等效频域数据频谱的“最佳匹配”的模型频谱。直接从HTFD-ML算法构造的信号模型中提取所需的幅值和频率参数。这里提出的HTFD-ML方法，如软件包CHIFIT所示，旨在应对D-维核磁共振数据集的模型拟合所带来的挑战，其中每个数据点由许多数据点(10(8)个并不罕见)组成，编码关于许多信号的信息(对于中等大小的蛋白质，高达10(5)个)呈现光谱重叠。通过对一系列测量N-15 T-1弛豫的二维H-1-N-15 HSQC实验的协调分析，证明了该方法的适用性。除了证明了对大的多维核磁共振谱进行极大似然分析的实用性，结果还表明，这种参数模型拟合方法比传统的基于峰值的FT谱分析提供了更准确的幅度和频率估计。模型拟合方法的改进性能源于它能够考虑拥挤频谱区域中所有信号的同时贡献(去卷积)，以及在构建模型以拟合数据时纳入先验知识。
A maximum likelihood (ML)-based approach has been established for the direct extraction of NMR parameters (e.g., frequency, amplitude, phase, and decay rate) simultaneously from all dimensions of a D-dimensional NMR spectrum. The approach, referred to here as HTFD-ML (hybrid time frequency domain maximum likelihood), constructs a time-domain model composed of a sum of exponentially-decaying sinusoidal signals. The apodized Fourier transform of this time-domain signal is a model spectrum that represents the 'best fit' to the equivalent frequency-domain data spectrum. The desired amplitude and frequency parameters can be extracted directly from the signal model constructed by the HTFD-ML algorithm. The HTFD-ML approach presented here, as embodied in the software package CHIFIT, is designed to meet the challenges posed by model fitting of D-dimensional NMR data sets, where each consists of many data points (10(8) is not uncommon) encoding information about numerous signals (up to 10(5) for a protein of moderate size) that exhibit spectral overlap. The suitability of the approach is demonstrated by its application to the concerted analysis of a series of ten 2D H-1-N-15 HSQC experiments measuring N-15 T-1 relaxation. In addition to demonstrating the practicality of performing maximum likelihood analysis on large, multidimensional NMR spectra, the results demonstrate that this parametric model-fitting approach provides more accurate amplitude and frequency estimates than those obtained from conventional peak-based analysis of the FT spectrum. The improved performance of the model fitting approach derives from its ability to take into account the simultaneous contributions of all signals in a crowded spectral region (deconvolution) as well as to incorporate prior knowledge in constructing models to fit the data.