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Reduced-dimensionality NMR spectroscopy for high-throughput protein resonance assignment

机译:降维NMR光谱用于高通量蛋白质共振分配

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摘要

A suite of reduced-dimensionality 13C,15N,1H-triple-resonance NMR experiments is presented for rapid and complete protein resonance assignment. Even when using short measurement times, these experiments allow one to retain the high spectral resolution required for efficient automated analysis. “Sampling limited” and “sensitivity limited” data collection regimes are defined, respectively, depending on whether the sampling of the indirect dimensions or the sensitivity of a multidimensional NMR experiments per se determines the minimally required measurement time. We show that reduced-dimensionality NMR spectroscopy is a powerful approach to avoid the “sampling limited regime”—i.e., a standard set of ten experiments proposed here allows one to effectively adapt minimal measurement times to sensitivity requirements. This is of particular interest in view of the greatly increased sensitivity of NMR spectrometers equipped with cryogenic probes. As a step toward fully automated analysis, the program autoassign has been extended to provide sequential backbone and 13Cβ resonance assignments from these reduced-dimensionality NMR data.
机译:提出了一整套降维 13 C, 15 N, 1 H三重共振NMR实验用于快速和完整的蛋白质共振分配。即使使用较短的测量时间,这些实验也可以保留有效的自动化分析所需的高光谱分辨率。分别根据间接维数的采样或多维NMR实验的灵敏度本身确定最小所需的测量时间来定义“采样受限”和“灵敏度受限”数据收集方案。我们表明,降维NMR光谱法是避免“采样受限方案”的有力方法,即,此处提出的一组标准实验(共十项)允许人们有效地将最小测量时间适应灵敏度要求。考虑到配备低温探针的NMR光谱仪的灵敏度大大提高,因此这特别有意义。作为朝着全自动分析迈出的一步,程序自动分配已经扩展,可以从这些降维NMR数据中提供顺序骨架和 13 C β共振分配。

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