Virtual and solution conformations of oligosaccharides.
The possibility that observed nuclear Overhauser enhancements and bulk longitudinal relaxation times, parameters measured by 1H NMR and often employed in determining the preferred solution conformation of biologically important molecules, are the result of averaging over many conformational states is quantitatively evaluated. Of particular interest was to ascertain whether certain 1H NMR determined conformations are "virtual" in nature; i.e., the fraction of the population of molecules actually found at any time within the subset of conformational space defined as the "solution conformation" is vanishingly small. A statistical mechanics approach was utilized to calculate an ensemble average relaxation matrix from which (NOE)'s and (T1)'s are calculated. Model glycosidic linkages in four oligosaccharides were studied. The solution conformation at any glycosidic linkage is properly represented by a normalized, Boltzmann distribution of conformers generated from an appropriate potential energy surface. The nature of the resultant population distributions is such that 50% of the molecular population is found within 1% of available microstates, while 99% of the molecular population occupies about 10% of the ensemble microstates, a number roughly equal to that sterically allowed. From this analysis we conclude that in many cases quantitative interpretation of NMR relaxation data, which attempts to define a single set of allowable torsion angle values consistent with the observed data, will lead to solution conformations that are either virtual or reflect torsion angle values possessed by a minority of the molecular population. On the other hand, calculation of ensemble average NMR relaxation data yields values in agreement with experimental results. Observed values of NMR relaxation data are the result of the complex interdependence of the population distribution and NOE (or T1) surfaces in conformational space. In conformational analyses, NMR data can therefore be used to test different population distributions calculated from empirical potential energy functions.
Cumming
D A
DA
Department of Medical Genetics, University of Toronto, Ontario, Canada.
Carver
J P
JP
D000465:Algorithms; D002236:Carbohydrate Conformation; D003198:Computer Simulation; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D008958:Models, Molecular; D009844:Oligosaccharides; D012996:Solutions
D009844:Oligosaccharides; D012996:Solutions