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Joint non-uniform sampling of all incremented time delays for quicker acquisition in protein relaxation studies

机译:对所有增加的时延进行联合非均匀采样以便在蛋白质松弛研究中更快地采集

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摘要

NMR relaxometry plays crucial role in studies of protein dynamics. The measurement of longitudinal and transverse relaxation rates of 15N is the main source of information on backbone motions. However, even the most basic approach exploiting a series of 15N HSQC spectra can require several hours of measurement time. Standard non-uniform sampling (NUS), i.e. random under-sampling of indirect time domain, typically cannot reduce this by more than 2–4 ×  due to relatively low “compressibility” of these spectra. In this paper we propose an extension of NUS to relaxation delays. The two-dimensional space of t1/trelax is sampled in a way similar to NUS of t1/t2 domain in 3D spectra. The signal is also processed in a way similar to that known from 3D NUS spectra i.e. using one of the most popular compressed sensing algorithms, iterative soft thresholding. The 2D Fourier transform matrix is replaced with mixed inverse Laplace-Fourier transform matrix. The peak positions in resulting 3D spectrum are characterized by two frequency coordinates and relaxation rate and thus no additional fitting of exponential curves is required. The method is tested on three globular proteins, providing satisfactory results in a time corresponding to acquisition of two conventional 15N HSQC spectra.
机译:NMR弛豫法在蛋白质动力学研究中起着至关重要的作用。 15 N的纵向和横向弛豫率的测量是有关骨干运动信息的主要来源。但是,即使是使用一系列 15 N HSQC光谱的最基本方法也需要数小时的测量时间。标准非均匀采样(NUS),即间接时域的随机欠采样,由于这些频谱的``可压缩性''相对较低,通常不能将其减少超过2-4倍。在本文中,我们提出将NUS扩展到弛豫延迟。以类似于3D光谱中t1 / t2域的NUS的方式对t1 / trelax的二维空间进行采样。信号的处理方式也类似于从3D NUS频谱已知的方式,即使用最流行的压缩传感算法之一,即迭代软阈值。将二维傅立叶变换矩阵替换为混合拉普拉斯-傅立叶逆变换矩阵。生成的3D频谱中的峰位置以两个频率坐标和弛豫率为特征,因此不需要额外拟合指数曲线。该方法在三种球状蛋白上进行了测试,在对应于两个常规 15 N HSQC谱图的采集时间内提供了令人满意的结果。

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