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 language | English (US) |
|---|---|
| Pages (from-to) | 103-110 |
| Number of pages | 8 |
| Journal | Journal of Magnetic Resonance |
| Volume | 214 |
| DOIs | |
| State | Published - Jan 1 2012 |
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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 journal › Article
}
TY - JOUR
T1 - FLAMEnGO
T2 - A fuzzy logic approach for methyl group assignment using NOESY and paramagnetic relaxation enhancement data
AU - Chao, Fa An
AU - Shi, Lei
AU - Masterson, Larry R.
AU - Veglia, Gianluigi
PY - 2012/1/1
Y1 - 2012/1/1
N2 - 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.
AB - 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.
KW - Automated assignment
KW - Fuzzy logic
KW - Methyl group assignments
KW - Methyl-TROSY
KW - Monte Carlo
KW - Sparse NMR data
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UR - http://www.scopus.com/inward/citedby.url?scp=84855677622&partnerID=8YFLogxK
U2 - 10.1016/j.jmr.2011.10.008
DO - 10.1016/j.jmr.2011.10.008
M3 - Article
C2 - 22134225
AN - SCOPUS:84855677622
VL - 214
SP - 103
EP - 110
JO - Journal of Magnetic Resonance
JF - Journal of Magnetic Resonance
SN - 1090-7807
ER -