NMR analysis of carbohydrates with model-free spectral densities: the dispersion range revisited

The impact of conformational sampling on first-principles calculations of vicinal COCH J-couplings in carbohydrates

Dihedral angles in organic molecules and biomolecules are vital structural parameters that can be indirectly probed by nuclear magnetic resonance (NMR) measurements of vicinal J-couplings. The empirical relations that map the measured couplings to dihedral angles are typically determined by fitting using static structural models, but this neglects the effects of thermal fluctuations at the finite temperature conditions under which NMR measurements are often taken. In this study, we calculate ensemble-averaged J-couplings for several structurally rigid carbohydrate derivatives using first-principles molecular dynamics simulations to sample the thermally accessible conformations around the minimum energy structure. Our results show that including thermal fluctuation effects significantly shifts the predicted couplings relative to single-point calculations at the energy minima, leading to improved agreement with experiments. This provides evidence that accounting for conformational sampling in first-principles calculations can improve the accuracy of NMR-based structure determination for structurally complex carbohydrates.

Limited Flexibility of Lactose Detected from Residual Dipolar Couplings Using Molecular Dynamics Simulations and Steric Alignment Methods

The conformational flexibility of lactose in solution has been investigated by residual dipolar couplings (RDCs). One-bond carbon-proton and proton-proton coupling constants have been measured in two oriented media and interpreted in combination with molecular dynamics simulations (MD). Two different approaches, known as PALES (Zweckstetter et al., J. Am. Chem. Soc. 2000, 122, 3791-3792) and TRAMITE (Azurmendi et al., J. Am. Chem. Soc. 2002, 124, 2426-2427), have been used to determine the alignment tensor from a shape-induced alignment model with the oriented medium. The steric alignment of the structures from several MD trajectories has provided ensemble averaged RDCs that have been compared with the experimental ones. The obtained results reveal the almost exclusive presence of a major low energy region defined as syn-phi/syn-psi (> 97%), for which sampling occurs in a dynamic manner. This result satisfactorily agrees with that determined by standard NOE-based methods.

Conformation and dynamics of heparin and heparan sulfate

The glycosaminoglycans heparin and heparan sulfate contain similar structural units in varying proportions providing considerable diversity in sequence and biological function. Both compounds are alternating copolymers of glucosamine with both iduronate- and glucuronate-containing sequences bearing N-sulfate, N-acetyl, and O-sulfate substitution. Protein recognition of these structurally-diverse compounds depends upon substitution pattern, overall molecular shape, and on internal mobility. In this review particular attention is paid to the dynamic aspects of heparin/heparan sulfate conformation. The iduronate residue possesses an unusually flexible pyranose ring conformation. This extra source of internal mobility creates special problems in rationalization of experimental data for these compounds. We present herein the solution-state NMR parameters, fiber diffraction data, crystallographic data, and molecular modeling methods employed in the investigation of heparin and heparan sulfate. Heparin is a useful model compound for the sulfated, protein-binding regions of heparan sulfate. The literature contains a number of solution and solid-state studies of heparin oligo- and polysaccharides for both isolated heparin species and those bound to protein receptors. These studies indicate a diversity of iduronate ring conformations, but a limited range of glycosidic linkage geometries in the repeating disaccharides. In this sense, heparin exhibits a well-defined overall shape within which iduronate ring forms can freely interconvert. Recent work suggests that computational modeling could potentially identify heparin binding sites on protein surfaces.