title: Facilitated assignment of large protein NMR signals with covariance sequential spectra using spectral derivatives.
abstract: Nuclear magnetic resonance (NMR) studies of larger proteins are hampered by difficulties in assigning NMR resonances. Human intervention is typically required to identify NMR signals in 3D spectra, and subsequent procedures depend on the accuracy of this so-called peak picking. We present a method that provides sequential connectivities through correlation maps constructed with covariance NMR, bypassing the need for preliminary peak picking. We introduce two novel techniques to minimize false correlations and merge the information from all original 3D spectra. First, we take spectral derivatives prior to performing covariance to emphasize coincident peak maxima. Second, we multiply covariance maps calculated with different 3D spectra to destroy erroneous sequential correlations. The maps are easy to use and can readily be generated from conventional triple-resonance experiments. Advantages of the method are demonstrated on a 37 kDa nonribosomal peptide synthetase domain subject to spectral overlap.
authors.affiliation: Department of Biophysics & Biophysical Chemistry, Johns Hopkins University School of Medicine , 701 Hunterian, 725 North Wolfe Street, Baltimore, Maryland 21205, United States.
authors.forename: Bradley J
authors.initials: BJ
authors.lastname: Harden
authors.forename: Scott R
authors.initials: SR
authors.lastname: Nichols
authors.forename: Dominique P
authors.initials: DP
authors.lastname: Frueh
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins