Solvent optimization and conformational flexibility effects on 1 H and 13 C NMR scaling factors

Epimeric Mixture Analysis and Absolute Configuration Determination Using an Integrated Spectroscopic and Computational Approach-A Case Study of Two Epimers of 6-Hydroxyhippeastidine

Structural elucidation has always been challenging, and misassignment remains a stringent issue in the field of natural products. The growing interest in discovering unknown, complex natural structures accompanies the increasing awareness concerning misassignments in the community. The combination of various spectroscopic methods with molecular modeling has gained popularity in recent years. In this work, we demonstrated, for the first time, its power to fully elucidate the 2-dimensional and 3-dimensional structures of two epimers in an epimeric mixture of 6-hydroxyhippeastidine. DFT calculation of chemical shifts was first performed to assist the assignment of planar structures. Furthermore, relative and absolute configurations were established by three different ways of computer-assisted structure elucidation (CASE) coupled with ORD/ECD/VCD spectroscopies. In addition, the significant added value of OR/ORD computations to relative and absolute configuration determination was also revealed. Remarkably, the differentiation of two enantiomeric scaffolds (crinine and haemanthamine) was accomplished via OR/ORD calculations with cross-validation by ECD and VCD.

Computational 1 H and 13 C NMR in structural and stereochemical studies

Present review outlines the advances and perspectives of computational ¹ H and ¹³ C NMR applied to the stereochemical studies of inorganic, organic, and bioorganic compounds, involving in particular natural products, carbohydrates, and carbonium ions. The first part of the review briefly outlines theoretical background of the modern computational methods applied to the calculation of chemical shifts and spin-spin coupling constants at the DFT and the non-empirical levels. The second part of the review deals with the achievements of the computational ¹ H and ¹³ C NMR in the stereochemical investigation of a variety of inorganic, organic, and bioorganic compounds, providing in an abridged form the material partly discussed by the author in a series of parent reviews. Major attention is focused herewith on the publications of the recent years, which were not reviewed elsewhere.

Reassignment of the structures of pestalopyrones A-D

Pestalopyrones A-D are four unusual tricyclic pyrone derivatives with flexible chiral structures, isolated from the endophytic fungus Pestalotiopsis neglecta S3. The full elucidation of their structures was a challenging task, and remained unsolved in the original article. Herein, the relative configurations of pestalopyrones A and pestalopyrones B were unambiguously assigned by detailed analyses on spectroscopic data and GIAO ¹³C NMR calculation method with sorted training sets (STS). The planar structures of pestalopyrones C and pestalopyrones D were revised by reinterpretation of their reported spectroscopic data, and then their relative configurations were deduced by STS GIAO ¹³C NMR calculation and NOE analysis. The absolute configurations of all the mentioned compounds were determined by the comparison of their experimental and calculated ECD curves.

Application of 1D 15 N and band-selective 2D 1 H-15 N CLIP-HSQMBC to detect 35/37 Cl isotope effect on nitrogen for unequivocal structure elucidation of the N-Cl moiety in molecules

An impurity, designated MS204, was isolated from a scale-up production of an intermediate toward the synthesis of an active pharmaceutical ingredient. Structural elucidation of this chloro-containing impurity was performed based on the analysis of the MS and NMR data. Band-selective 2D ¹ H-¹⁵ N CLIP-HSQMBC experiment was developed to unequivocally identify the ionic N-Cl moiety in the molecule by discovering the two isotope-shifted nitrogen peaks as 3 to 1 ratio separated by about ¹ Δ¹⁵ N(^37/35 Cl) = 19.6 ppb (1.19 Hz) due to the Cl isotope effect. 1D ¹⁵ N and 2D ¹ H-¹⁵ N CLIP-HSQMBC experiments were applied to commercially available compounds to further confirm the techniques by detecting the isotope shift of nitrogen peaks for the N-Cl moiety in molecules.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Structural characterisation of natural products by means of quantum chemical calculations of NMR parameters: new insights

In this review, we focus in all aspects of NMR simulation of natural products, from the fundamentals to the new computational toolboxes available, combining advanced quantum chemical calculations with upstream data processing and machine learning.