The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications.

The anisotropy of rapid fluctuations of the peptide planes in ubiquitin is explored by combined 15N and 13C‘ nuclear spin relaxation measurements and molecular dynamics (MD) computer simulation. T 1, T 2, and NOE data were collected at B 0-field strenghts corresponding to 400 and 600 MHz proton resonance. A 1.5-ns simulation of ubiquitin in an explicit water environment was performed using CHARMM 24. The simulation suggests that, for 76% of the peptide planes, the relaxation-active motion of the backbone 15N and 13C‘ spins is dominated by anisotropic Gaussian axial fluctuations of the peptide planes about three orthogonal axes. The dominant fluctuation axes are nearly parallel to the − axes. The remaining peptide planes belong to more flexible regions of the backbone and cannot be described by this type of motion alone. Based on the results of the computer simulation, an analytical 3D GAF motional model (Bremi, T.; Brüschweiler, R. J. Am. Chem. Soc. 1997, 119, 6672−6673) was applied to the experimental relaxation data. The fluctuation amplitudes of the peptide planes show a significant anisotropy of the internal motion. This analysis demonstrates that a combined interpretation of 15N and 13C‘ relaxation data by a model derived from a computer simulation may provide detailed insight into the fast time-scale backbone dynamics that goes beyond the results of a standard model-free analysis.

Despite their importance for biological activity, slower molecular motions beyond the nanosecond range remain poorly understood. We have assembled an unprecedented set of experimental NMR data, comprising up to 27 residual dipolar couplings per amino acid, to define the nature and amplitude of backbone motion in protein G using the Gaussian axial fluctuation model in three dimensions. Slower motions occur in the loops, and in the ␤-sheet, and are absent in other regions of the molecule, including the ␣-helix. In the ␤-sheet an alternating pattern of dynamics along the peptide sequence is found to form a long-range network of slow motion in the form of a standing wave extending across the ␤-sheet, resulting in maximal conformational sampling at the interaction site. The alternating nodes along the sequence match the alternation of strongly hydrophobic side chains buried in the protein core. Confirmation of the motion is provided through extensive crossvalidation and by independent hydrogen-bond scalar coupling analysis that shows this motion to be correlated. These observations strongly suggest that dynamical information can be transmitted across hydrogen bonds and have important implications for understanding collective motions and long-range information transfer in proteins.protein dynamics ͉ slow motions ͉ correlated M olecular dynamics, manifest in backbone and side-chain mobilities, play a crucial role in protein stability and function (1-4). The accurate characterization and understanding of protein motions thus adds an additional dimension to the structural information derived from genomics projects (5, 6). Although local backbone fluctuations on the picosecond to nanosecond time scale have been the subject of detailed characterization using NMR (7, 8) and molecular dynamics simulations (2), slower motions, in the submicrosecond to second range, remain poorly understood. Relaxation dispersion has been used to successfully identify sites of conformational exchange between states experiencing different chemical shifts in peptides (9) and proteins (10), but specific geometric motional models are often difficult to extract from these data. Slow time scales are, however, of particular interest because functionally important biological processes, including enzyme catalysis (11), signal transduction (12), ligand binding, and allosteric regulation (13), as well as collective motions involving groups of atoms or whole amino acids (14), are expected to occur in this time range. Residual dipolar couplings (RDCs) report on averages over longer time scales (up to the millisecond range) and therefore encode key information for understanding slower protein motions over a very broad time scale (15,16). Recent studies have exploited the orientational averaging properties of RDCs to characterize the amplitude and direction of motions of NH vectors (17)(18)(19) or to study local variations in position and dynamics of the amide proton (20,21). Despite this activity, key questions remain concerning the nature and amplitude of ...