ArticleJournal of the American Chemical Society2014
Facilitated assignment of large protein NMR signals with covariance sequential spectra using spectral derivatives.
Article in Journal of the American Chemical Society, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Minimizing Pervasive Artifacts in 4D Covariance Maps for Protein Side Chain NMR Assignments.The journal of physical chemistry. A · 2021Article
- SMolESY: an efficient and quantitative alternative to on-instrument macromolecularChemical science · 2020Article
- Emerging solution NMR methods to illuminate the structural and dynamic properties of proteins.Current opinion in structural biology · 2019Review
- Optimal control theory enables homonuclear decoupling without Bloch-Siegert shifts in NMR spectroscopy.Nature communications · 2018Article
- Covariance nuclear magnetic resonance methods for obtaining protein assignments and novel correlations.Concepts in magnetic resonance. Part A, Bridging education and research · 2017Article
- Effortless assignment with 4D covariance sequential correlation maps.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2015Article
- Assignment of methyl NMR resonances of a 52 kDa protein with residue-specific 4D correlation maps.Journal of biomolecular NMR · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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.
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Registered trials
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