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 coworkers [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 resonance 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.

FLAMEnGO 2.0: An enhanced fuzzy logic algorithm for structure-based assignment of methyl group resonances

“…The deviations from the experimental and the calculated methyl chemical shifts were minimized using the chemical shift matching function described previously (Fig. 2A) [12]. Residue-type assignments were performed using selective amino acid labeling and mapped with CT-HMQC experiments.…”

“…The MTSSL excess was removed by filtration. To quantify the PREs, two separate experiments were performed with both oxidized and reduced kinase as described previously [12]. …”

“…All of the original matching functions are reported in our previous work [12]. The new implementations for FLAMEnGO 2.0 are summarized in the following synopsis.…”

“…Due to errors in phasing the 3D spectra or lack of resolution in the 3D spectra, NOE cross peaks between two methyl groups can have proton and carbon chemical shifts that differ slightly from those of the methyl groups. In the previous version of the algorithm [12], these differences in chemical shifts affected the score, even if these peaks were unambiguously assigned and located in well-resolved regions of the spectrum. To avoid this problem, we assigned scores for cross peaks located in a well-resolved region higher than those for cross peaks located in crowded regions.…”

“…MAP-XS utilizes a pre-existing protein X-ray structure and exploits methyl-methyl NOESY networks to assign the methyl group resonances. Building on this approach, we previously developed a new and more efficient algorithm based on fuzzy logic and Monte Carlo sampling (FLAMEnGO or Fuzzy Logic Assignment of Methyl Group) that dramatically improved the accuracy (correctness) of the resonance assignment [12]. …”