Kancherla Aswani K, Frueh Dominique P
Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Concepts Magn Reson Part A Bridg Educ Res. 2017 Mar;46A(2). doi: 10.1002/cmr.a.21437. Epub 2018 Sep 16.
Protein NMR resonance assignment can be a tedious and error prone process, and it is often a limiting factor in biomolecular NMR studies. Challenges are exacerbated in larger proteins, disordered proteins, and often alpha-helical proteins, owing to an increase in spectral complexity and frequency degeneracies. Here, several multi-dimensional spectra must be inspected and compared in an iterative manner before resonances can be assigned with confidence. Over the last two decades, covariance NMR has evolved to become applicable to protein multi-dimensional spectra. The method, previously used to generate new correlations from spectra of small organic molecules, can now be used to recast assignment procedures as mathematical operations on NMR spectra. These operations result in multidimensional correlation maps combining all information from input spectra and providing direct correlations between moieties that would otherwise be compared indirectly through reporter nuclei. Thus, resonances of sequential residues can be identified and side-chain signals can be assigned by visual inspection of 4D arrays. This review highlights advances in covariance NMR that permitted to generate reliable 4D arrays and describes how these arrays can be obtained from conventional NMR spectra.
蛋白质核磁共振共振归属可能是一个繁琐且容易出错的过程,并且它常常是生物分子核磁共振研究中的一个限制因素。在较大的蛋白质、无序蛋白质以及通常的α螺旋蛋白质中,由于光谱复杂性和频率简并性的增加,挑战会更加严峻。在此,在能够自信地归属共振之前,必须以迭代的方式检查和比较几个多维光谱。在过去二十年中,协方差核磁共振已发展到适用于蛋白质多维光谱。该方法以前用于从小有机分子的光谱中生成新的相关性,现在可用于将归属程序重塑为对核磁共振光谱的数学运算。这些运算会产生多维相关图,将来自输入光谱的所有信息结合起来,并提供原本要通过报告核间接比较的部分之间的直接相关性。因此,通过对四维阵列的目视检查可以识别连续残基的共振并归属侧链信号。本综述重点介绍了协方差核磁共振在生成可靠的四维阵列方面取得的进展,并描述了如何从传统核磁共振光谱中获得这些阵列。