Over the last 20 years, the number of large proteins accessible to protein-NMR analysis has increased significantly due to the development of selective 1H,13C-methyl labelling techniques in combination with methyl-TROSY based NMR experiments. Structure-based strategies for the assignment of ¹H,¹³C-methyl groups rely on comparing spatial constraints derived from methyl–methyl NOEs to a known three-dimensional structure of the protein of interest. Cross peaks in methyl-TROSY spectra are assigned to specific methyl groups by matching methyl–methyl NOEs, as observed for example in 4D HMQC-NOESY-HMQC spectra, with distances derived from a structural model. This process is commonly referred to as a “methyl walk”. Here, we present AMIGO (Automated Methyl assignment via Iterative Graph Optimization), a novel assignment algorithm that formalises the intuitive methyl walk procedure by constructing graphs with nodes representing specific methyl groups and edges reflecting methyl-methyl NOEs or short methyl-methyl distances in a model. “Building blocks” consisting of nodes and edges are then generated to reconcile structure-based and NOE-based graphs. Assignments are achieved through permutation and concatenation of individual “building blocks” in a modular fashion, enabling efficient computation even for large proteins. Additional experimental restraints, such as paramagnetic relaxation enhancements (PREs) or pseudocontact shifts (PCSs), can be integrated to validate and extend the assignments. The performance of AMIGO was validated using 11 proteins that had previously been assigned and 32 NOE networks that had been generated synthetically.
Maass et al. (Mon,) studied this question.