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Automatic structure-based NMR methyl resonance assignment in large proteins

Author

Listed:
  • Iva Pritišanac

    (Goethe University Frankfurt am Main)

  • Julia M. Würz

    (Goethe University Frankfurt am Main)

  • T. Reid Alderson

    (NIDDK, National Institutes of Health)

  • Peter Güntert

    (Goethe University Frankfurt am Main
    ETH Zürich
    Tokyo Metropolitan University)

Abstract

Isotopically labeled methyl groups provide NMR probes in large, otherwise deuterated proteins. However, the resonance assignment constitutes a bottleneck for broader applicability of methyl-based NMR. Here, we present the automated MethylFLYA method for the assignment of methyl groups that is based on methyl-methyl nuclear Overhauser effect spectroscopy (NOESY) peak lists. MethylFLYA is applied to five proteins (28–358 kDa) comprising a total of 708 isotope-labeled methyl groups, of which 612 contribute NOESY cross peaks. MethylFLYA confidently assigns 488 methyl groups, i.e. 80% of those with NOESY data. Of these, 459 agree with the reference, 6 were different, and 23 were without reference assignment. MethylFLYA assigns significantly more methyl groups than alternative algorithms, has an average error rate of 1%, modest runtimes of 0.4–1.2 h, and can handle arbitrary isotope labeling patterns and data from other types of NMR spectra.

Suggested Citation

  • Iva Pritišanac & Julia M. Würz & T. Reid Alderson & Peter Güntert, 2019. "Automatic structure-based NMR methyl resonance assignment in large proteins," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12837-8
    DOI: 10.1038/s41467-019-12837-8
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    Cited by:

    1. Anthony C. Bishop & Glorisé Torres-Montalvo & Sravya Kotaru & Kyle Mimun & A. Joshua Wand, 2023. "Robust automated backbone triple resonance NMR assignments of proteins using Bayesian-based simulated annealing," Nature Communications, Nature, vol. 14(1), pages 1-15, December.

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