Automatic structure-based NMR methyl resonance assignment in large proteins

Methyl groups provide crucial NMR probes for investigating protein structure, dynamics and mechanisms in systems that are too large for NMR with uniform isotope labeling. This requires the assignment of methyl signals in the NMR spectra to specific methyl groups in the protein, an expensive and time-consuming endeavor that limits the use of methyl-based NMR for large proteins. To resolve this bottleneck, several methyl resonance assignment methods have been developed. These approaches remain limited with regard to complete automation and/or the extent and accuracy of the assignments. Here, we present the completely automated MethylFLYA method for the assignment of methyl groups. MethylFLYA requires as input exclusively methyl-methyl nuclear Overhauser effect spectroscopy (NOESY) peak lists. The algorithm was applied to five proteins of 28-358 kDa mass with a total of 708 isotope-labeled methyl groups. Manually made 1H/13C reference assignments were available for 674 methyls. The available experimental peak lists contained NOESY cross peaks for 614 methyls. MethylFLYA confidently assigned 488 methyls, i.e. 79% of those with NOESY data. Of these assignments, 460 agreed with the reference, 5 were different (and 23 concerned methyls without reference assignment). For three proteins of 28, 81, and 358 kDa, all confident assignments by MethylFLYA were correct. We furthermore show that, for high-quality NOESY spectra, automatic picking of NOE signals followed by resonance assignment with MethylFLYA can yield results that are comparable to those obtained for manually prepared peak lists, indicating the feasibility of unbiased, fully automatic methyl resonance assignment starting directly from the NMR spectra. This renders MethylFLYA an advantageous alternative to existing approaches for structure-based methyl assignment. MethylFLYA assigns, for most proteins, significantly more methyl groups than other algorithms, has an average error rate of 1%, modest runtimes of 0.4-1.2 h for the five proteins, and flexibility to handle arbitrary isotope labeling patterns and include data from other types of NMR spectra.