Facilitated assignment of large protein NMR signals with covariance sequential spectra using spectral derivatives

Bradley J. Harden, Scott R. Nichols, Dominique P. Frueh

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)13106-13109
Number of pages4
JournalJournal of the American Chemical Society
Volume136
Issue number38
DOIs
StatePublished - Sep 24 2014

ASJC Scopus subject areas

  • Catalysis
  • Chemistry(all)
  • Biochemistry
  • Colloid and Surface Chemistry

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