Structure determination of slowly exchanging conformers in solution using high-resolution NMR, computational modeling and DFT-GIAO chemical shielding: application to an erythronolide A derivative

Pseudocyclic Form of 4-Hydroxypyrrolidine-2-carboxanilide Podands with Trioxyethylene Chain: Modeling, Conformational Search, and NMR Analysis

The 4-hydroxypyrrolidine-2-carboxanilide podand salt demonstrates catalytic activity in asymmetric Biginelli reaction. The systematic search for prevalent conformational state of the cation was carried out by computer simulations in combination with one- and two-dimensional NMR experiments. For that purpose, we proposed a novel algorithm for the generation and selection of conformers based on molecular dynamics and clustering in the space of principal components. The search had found an important trend of the podand to form a pseudocyclic structure with a horseshoe-shaped conformation of the oligooxyethylene fragment. This conformation is stabilized by different types of intramolecular hydrogen bonds between the acidic and basic centers of the two 4-hydroxypyrrolidine-2-carboxanilide residuals (branches). The proposed approach had made it possible to identify the major structural factors, providing a correlation between the calculated and experimental chemical shifts of hydrogen atoms in the ¹H NMR spectra of the protonated podand.

Exploratory machine-learned theoretical chemical shifts can closely predict metabolic mixture signals

Various chemical shift predictive methodologies have been studied and developed, but there remains the problem of prediction accuracy. Assigning the NMR signals of metabolic mixtures requires high predictive performance owing to the complexity of the signals. Here we propose a new predictive tool that combines quantum chemistry and machine learning. A scaling factor as the objective variable to correct the errors of 2355 theoretical chemical shifts was optimized by exploring 91 machine learning algorithms and using the partial structure of 150 compounds as explanatory variables. The optimal predictive model gave RMSDs between experimental and predicted chemical shifts of 0.2177 ppm for δ 1H and 3.3261 ppm for δ 13C in the test data; thus, better accuracy was achieved compared with existing empirical and quantum chemical methods. The utility of the predictive model was demonstrated by applying it to assignments of experimental NMR signals of a complex metabolic mixture.

Fragment Assembly Approach Based on Graph/Network Theory with Quantum Chemistry Verifications for Assigning Multidimensional NMR Signals in Metabolite Mixtures

The abundant observation of chemical fragment information for molecular complexities is a major advantage of biological NMR analysis. Thus, the development of a novel technique for NMR signal assignment and metabolite identification may offer new possibilities for exploring molecular complexities. We propose a new signal assignment approach for metabolite mixtures by assembling H-H, H-C, C-C, and Q-C fragmental information obtained by multidimensional NMR, followed by the application of graph and network theory. High-speed experiments and complete automatic signal assignments were achieved for 12 combined mixtures of (13)C-labeled standards. Application to a (13)C-labeled seaweed extract showed 66 H-C, 60 H-H, 326 C-C, and 28 Q-C correlations, which were successfully assembled to 18 metabolites by the automatic assignment. The validity of automatic assignment was supported by quantum chemical calculations. This new approach can predict entire metabolite structures from peak networks of biological extracts.

The Effect of Molecular Conformation on the Accuracy of Theoretical (1)H and (13)C Chemical Shifts Calculated by Ab Initio Methods for Metabolic Mixture Analysis

NMR spectroscopy is a powerful method for analyzing metabolic mixtures. The information obtained from an NMR spectrum is in the form of physical parameters, such as chemical shifts, and construction of databases for many metabolites will be useful for data interpretation. To increase the accuracy of theoretical chemical shifts for development of a database for a variety of metabolites, the effects of sets of conformations (structural ensembles) and the levels of theory on computations of theoretical chemical shifts were systematically investigated for a set of 29 small molecules in the present study. For each of the 29 compounds, 101 structures were generated by classical molecular dynamics at 298.15 K, and then theoretical chemical shifts for 164 (1)H and 123 (13)C atoms were calculated by ab initio quantum chemical methods. Six levels of theory were used by pairing Hartree-Fock, B3LYP (density functional theory), or second order Møller-Plesset perturbation with 6-31G or aug-cc-pVDZ basis set. The six average fluctuations in the (1)H chemical shift were ±0.63, ± 0.59, ± 0.70, ± 0.62, ± 0.75, and ±0.66 ppm for the structural ensembles, and the six average errors were ±0.34, ± 0.27, ± 0.32, ± 0.25, ± 0.32, and ±0.25 ppm. The results showed that chemical shift fluctuations with changes in the conformation because of molecular motion were larger than the differences between computed and experimental chemical shifts for all six levels of theory. In conclusion, selection of an appropriate structural ensemble should be performed before theoretical chemical shift calculations for development of an accurate database for a variety of metabolites.

SENSI: signal enhancement by spectral integration for the analysis of metabolic mixtures

The method provided here can overcome the low S/N problem in ¹³C NMR by the integration of plural spectra to increase the resolution based on non-bucketing analysis without measurements.

New and old NMR experiments for the resonance assignment of complex oligosaccharides--application to a cyclodextrin derivative

The complete assignment of the (1)H and (13)C sugar resonances in mono-3,6-anhydro-heptakis(2,3-O-methyl)-hexakis(6-O-methyl)-β-cyclodextrin, an asymmetrically functionalized β-cyclodextrin, was carried out by means of 2D NMR experiments. The TOCSY and the homonuclear multiple relay COSY spectra provided most of the (1)H assignments. The multiplicity edited HSQC and a set of F(1) selective HSQC-TOCSY and multiple relay HSQC-COSY spectra gave access to most of the (13)C chemical shifts. The latter were fully and accurately determined by means of a pair of complementary, highly folded HSQC-TOCSY spectra. The TOCSY-ROESY and ROESY-TOCSY spectra yielded the sequential assignment of the sugar units. A high resolution F(1) selective F(1) decoupled version of the TOCSY-ROESY experiment was recorded.