Covariance nuclear magnetic resonance methods for obtaining protein assignments and novel correlations

Abstract

Protein nuclear magnetic resonance (NMR) 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 multidimensional spectra must be inspected and compared in an iterative manner before resonances can be assigned with confidence. Over the last 2 decades, covariance NMR has evolved to become applicable to protein multidimensional 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.