Progress toward automated methyl assignments for methyl-TROSY applications

Methyl-TROSY spectroscopy has extended the reach of solution-state NMR to supra-molecular machineries over 100 kDa in size. Methyl groups are ideal probes for studying structure, dynamics, and protein-protein interactions in quasi-physiological conditions with atomic resolution. Successful implementation of the methodology requires accurate methyl chemical shift assignment, and the task still poses a significant challenge in the field. In this work, we outline the current state of technology for methyl labeling, data collection, data analysis, and nuclear Overhauser effect (NOE)-based automated methyl assignment approaches. We present MAGIC-Act and MAGIC-View, two Python extensions developed as part of the popular NMRFAM-Sparky package, and MAGIC-Net a standalone structure-based network analysis program. MAGIC-Act conducts statistically driven amino acid typing, Leu/Val pairing guided by 3D HMBC-HMQC, and NOESY cross-peak symmetry checking. MAGIC-Net provides model-based NOE statistics to aid in selection of a methyl labeling scheme. The programs provide a versatile, semi-automated framework for rapid methyl assignment.