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


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.

SUBMITTER: Chao FA 

PROVIDER: S-EPMC3487468 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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

Chao Fa-An FA   Shi Lei L   Masterson Larry R LR   Veglia Gianluigi G  

Journal of magnetic resonance (San Diego, Calif. : 1997) 20111020 1


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 per  ...[more]

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