FLAMEnGO: A fuzzy logic approach for methyl group assignment using NOESY and paramagnetic relaxation enhancement data

Fa An Chao, Lei Shi, Larry R. Masterson, Gianluigi Veglia

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Building on a recent method by Matthews and co-workers [1], we developed a new and efficient algorithm to assign methyl resonances from sparse and ambiguous NMR data. The new algorithm (FLAMEnGO: Fuzzy Logic Assignment of MEthyl GrOups) uses Monte Carlo sampling in conjunction with fuzzy logic to obtain the assignment of methyl resonances at high fidelity. Furthermore, we demonstrate that the inclusion of paramagnetic relaxation enhancement (PRE) data in the assignment strategy increases the percentage of correct assignments with sparse NOE data. Using synthetic tests and experimental data we show that this new approach provides up to ∼80% correct assignments with only 30% of methyl-methyl NOE data. In the experimental case of ubiquitin, PRE data from two spin labeled sites improve the percentage of assigned methyl groups up to ∼91%. This new strategy promises to further expand methyl group NMR spectroscopy to very large macromolecular systems.

Original languageEnglish (US)
Pages (from-to)103-110
Number of pages8
JournalJournal of Magnetic Resonance
Volume214
DOIs
StatePublished - Jan 2012

Bibliographical note

Funding Information:
This work was supported by the National Institute of Health (GM072701 to G.V. and T32DE007288 to L.R.M.). We also would like to thank Dr. Marco Tonelli at NMRFAM for assistance with the NMR spectroscopy. The scripts and instructions for FLAMEnGO are available at www.chem.umn.edu/groups/veglia under “downloads”.

Keywords

  • Automated assignment
  • Fuzzy logic
  • Methyl group assignments
  • Methyl-TROSY
  • Monte Carlo
  • Sparse NMR data

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