Enhancing solution structural analysis of large molecular proteins through optimal stereo array isotope labeling of aromatic amino acids

The observation of side-chain peaks of aromatic amino acids is the prerequisite for a high-resolution three-dimensional structure determination of proteins by NMR. However, it becomes difficult with increasing molecular size due to an increased transverse relaxation and the control of the relaxation pathway is needed to achieve the observation. We demonstrated that even for the large molecular size of 82 kDa Malate synthase G (MSG), the aromatic ¹³C-¹H (CH) peaks of Tryptophan (Trp) and Phenylalanine (Phe) residues can be observed with high quality using a systematic stable isotope labeling scheme, Stereo-Array Isotope Labeling (SAIL) method. However, the sequence specific assignments of these peaks relied on the use of amino acid substitutions, employing an inefficient method that required many isotopes labeled samples. In this study, we developed novel SAIL amino acids that allow for the observation of the aromatic ring δ,ζ and the aliphatic β position peak of Phe residues. The application of TROSY-based experiment to the isolated CH moieties resulted in the successful observation of discernible and resolved CH peaks in Phe residues in MSG. In MSG, the sequence-specific assignments of the backbone and C_β positions have already been confirmed. Therefore, using this labeling method, the δ and β position peaks of Phe residues can be clearly assigned in a sequence-specific and stereospecific manner through experiments based on intra-residue NOE. Furthermore, the NOESY experiment also allows for the acquisition of information pertaining to the conformation of Phe residues, such as the χ1 dihedral angle, providing valuable insights for the determination of accurate protein structures and in dynamic analysis. This new SAIL amino acids open an avenue to achieve a variety of NMR analysis of large molecular proteins, including a high-resolution structure determination and dynamics and interaction analysis.