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 journalArticle

18 Citations (Scopus)

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 1 2012

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Fuzzy Logic
Fuzzy logic
logic
augmentation
Ubiquitin
Nuclear magnetic resonance spectroscopy
Magnetic Resonance Spectroscopy
Nuclear magnetic resonance
Sampling
nuclear magnetic resonance
sampling
inclusions
spectroscopy

Keywords

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

Cite this

FLAMEnGO : A fuzzy logic approach for methyl group assignment using NOESY and paramagnetic relaxation enhancement data. / Chao, Fa An; Shi, Lei; Masterson, Larry R.; Veglia, Gianluigi.

In: Journal of Magnetic Resonance, Vol. 214, 01.01.2012, p. 103-110.

Research output: Contribution to journalArticle

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