Berjanskii Mark V, Wishart David S
Departments of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E8.
J Am Chem Soc. 2005 Nov 2;127(43):14970-1. doi: 10.1021/ja054842f.
Protein motions play a critical role in many biological processes, such as enzyme catalysis, allosteric regulation, antigen-antibody interactions, and protein-DNA binding. NMR spectroscopy occupies a unique place among methods for investigating protein dynamics due to its ability to provide site-specific information about protein motions over a large range of time scales. However, most NMR methods require a detailed knowledge of the 3D structure and/or the collection of additional experimental data (NOEs, T1, T2, etc.) to accurately measure protein dynamics. Here we present a simple method based on chemical shift data that allows accurate, quantitative, site-specific mapping of protein backbone mobility without the need of a three-dimensional structure or the collection and analysis of NMR relaxation data. Further, we show that this chemical shift method is able to quantitatively predict per-residue RMSD values (from both MD simulations and NMR structural ensembles) as well as model-free backbone order parameters.
蛋白质运动在许多生物过程中起着关键作用，如酶催化、别构调节、抗原-抗体相互作用以及蛋白质-DNA结合。核磁共振波谱法在研究蛋白质动力学的方法中占据独特地位，因为它能够在大范围的时间尺度上提供有关蛋白质运动的位点特异性信息。然而，大多数核磁共振方法需要详细了解三维结构和/或收集额外的实验数据（核Overhauser效应、T1、T2等）来准确测量蛋白质动力学。在此，我们提出一种基于化学位移数据的简单方法，该方法无需三维结构，也无需收集和分析核磁共振弛豫数据，就能对蛋白质主链流动性进行准确、定量、位点特异性的映射。此外，我们表明这种化学位移方法能够定量预测每个残基的均方根偏差值（来自分子动力学模拟和核磁共振结构集合）以及无模型主链序参数。
