Applying computer-assisted structure elucidation algorithms for the purpose of structure validation: revisiting the NMR assignments of hexacyclinol

DELTA50: A Highly Accurate Database of Experimental 1H and 13C NMR Chemical Shifts Applied to DFT Benchmarking

Density functional theory (DFT) benchmark studies of ¹H and ¹³C NMR chemical shifts often yield differing conclusions, likely due to non-optimal test molecules and non-standardized data acquisition. To address this issue, we carefully selected and measured ¹H and ¹³C NMR chemical shifts for 50 structurally diverse small organic molecules containing atoms from only the first two rows of the periodic table. Our NMR dataset, DELTA50, was used to calculate linear scaling factors and to evaluate the accuracy of 73 density functionals, 40 basis sets, 3 solvent models, and 3 gauge-referencing schemes. The best performing DFT methodologies for ¹H and ¹³C NMR chemical shift predictions were WP04/6-311++G(2d,p) and ωB97X-D/def2-SVP, respectively, when combined with the polarizable continuum solvent model (PCM) and gauge-independent atomic orbital (GIAO) method. Geometries should be optimized at the B3LYP-D3/6-311G(d,p) level including the PCM solvent model for the best accuracy. Predictions of 20 organic compounds and natural products from a separate probe set had root-mean-square deviations (RMSD) of 0.07 to 0.19 for ¹H and 0.5 to 2.9 for ¹³C. Maximum deviations were less than 0.5 and 6.5 ppm for ¹H and ¹³C, respectively.

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.

DFT Calculations of 1H- and 13C-NMR Chemical Shifts of Geometric Isomers of Conjugated Linoleic Acid (18:2 ω-7) and Model Compounds in Solution

A density functional theory (DFT) study of the ¹H- and ¹³C-NMR chemical shifts of the geometric isomers of 18:2 ω-7 conjugated linoleic acid (CLA) and nine model compounds is presented, using five functionals and two basis sets. The results are compared with available experimental data from solution high resolution nuclear magnetic resonance (NMR). The experimental ¹H chemical shifts exhibit highly diagnostic resonances due to the olefinic protons of the conjugated double bonds. The "inside" olefinic protons of the conjugated double bonds are deshielded than those of the "outside" protons. Furthermore, in the cis/trans isomers, the signals of the cis bonds are more deshielded than those of the trans bonds. These regularities of the experimental ¹H chemical shifts of the olefinic protons of the conjugated double bonds are reproduced very accurately for the lowest energy DFT optimized single conformer, for all functionals and basis sets used. The other low energy conformers have negligible effects on the computational ¹H-NMR chemical shifts. We conclude that proton NMR chemical shifts are more discriminating than carbon, and DFT calculations can provide a valuable tool for (i) the accurate prediction of ¹H-NMR chemical shifts even with less demanding functionals and basis sets; (ii) the unequivocal identification of geometric isomerism of CLAs that occur in nature, and (iii) to derive high resolution structures in solution.

Enzymatic Reconstitution and Biosynthetic Investigation of the Bacterial Carbazole Neocarazostatin A

Tricyclic carbazole is an important scaffold in many naturally occurring metabolites, as well as valuable building blocks. Here we report the reconstitution of the ring A formation of the bacterial neocarazostatin A carbazole metabolite. We provide evidence of the involvement of two unusual aromatic polyketide proteins. This finding suggests how new enzymatic activities can be recruited to specific pathways to expand biosynthetic capacities. Finally, we leveraged our bioinformatics survey to identify the untapped capacity of carbazole biosynthesis.

Questions in natural products synthesis research that can (and cannot) be answered using computational chemistry

Questions of relevance to those working in the field of natural products synthesis that can be answered, at least in part, using computational chemistry approaches are described. Illustrative examples are provided, as are descriptions of limitations.

Evaluation of the Factors Impacting the Accuracy of 13C NMR Chemical Shift Predictions using Density Functional Theory-The Advantage of Long-Range Corrected Functionals

The various factors influencing the accuracy of ¹³C NMR calculations using density functional theory (DFT), including the basis set, exchange-correlation (XC) functional, and isotropic shielding calculation method, are evaluated. A wide selection of XC functionals (over 70) were considered, and it was found that long-range corrected functionals offer a significant improvement over the other classes of functionals. Based on a thorough study, it is recommended that for calculating NMR chemical shifts (δ) one should use the CSGT method, the COSMO solvation model, and the LC-TPSSTPSS exchange-correlation functional in conjunction with the cc-pVTZ basis set. A selection of problems in natural product identification are considered in light of the newly recommended level of theory.

Dereplication: racing to speed up the natural products discovery process

Covering: 1993-2014 (July)To alleviate the dereplication holdup, which is a major bottleneck in natural products discovery, scientists have been conducting their research efforts to add tools to their "bag of tricks" aiming to achieve faster, more accurate and efficient ways to accelerate the pace of the drug discovery process. Consequently dereplication has become a hot topic presenting a huge publication boom since 2012, blending multidisciplinary fields in new ways that provide important conceptual and/or methodological advances, opening up pioneering research prospects in this field.

Natural products with anti-Bredt and bridgehead double bonds

Well over a hundred years ago, Professor Julius Bredt embarked on a career pursuing and critiquing bridged bicyclic systems that contained ring strain induced by the presence of a bridgehead olefin. These endeavors founded what we now know as Bredt's rule (Bredtsche Regel). Physical, theoretical, and synthetic organic chemists have intensely studied this premise, pushing the boundaries of such systems to arrive at a better understood physical phenomenon. Mother nature has also seen fit to construct molecules containing bridgehead double bonds that encompass Bredt's rule. For the first time, this topic is reviewed in a natural product context.

Recent advances in the structure elucidation of small organic molecules by the LSD software

The LSD software proposes the structures of small organic molecules that fit with structural constraints from 1D and 2D NMR spectroscopy. Its initial design introduced limits that needed to be eliminated to extend its scope and help its users choose the most likely structure among those proposed. The LSD software code has been improved, so that it recognizes a wider set of atom types to build molecules. More flexibility has been given in the interpretation of 2D NMR data, including the automatic detection of very long-range correlations. A program named pyLSD was written to deal with problems in which atom types are ambiguously defined. It also provides a (13)C NMR chemical shift-based solution ranking algorithm. PyLSD was able to propose the correct structure of hexacyclinol, a natural product whose structure determination has been highly controversal. The solution was ranked first within a list of ten structures that were produced by pyLSD from the literature NMR data. The structure of an aporphin natural product was determined by pyLSD, taking advantage of the possibility of handling electrically charged atoms. The structure generation of the insect antifeedant azadirachtin by LSD was reinvestigated by pyLSD, considering that three (13)C resonances did not lead to univocal hybridization states.

Using NMR to identify and characterize natural products

Over the past 28 years there have been several thousand publications describing the use of 2D NMR to identify and characterize natural products. During this time period, the amount of sample needed for this purpose has decreased from the 20-50 mg range to under 1 mg. This has been due to both improvements in NMR hardware and methodology. This review will focus on mainly methodology improvements, particularly in pulse sequences, acquisition and processing methods which are particularly relevant to natural product research, with lesser discussion of hardware improvements.

Structure revision of asperjinone using computer-assisted structure elucidation methods

The elucidated structure of asperjinone (1), a natural product isolated from thermophilic Aspergillus terreus, was revised using the expert system Structure Elucidator. The reliability of the revised structure (2) was confirmed using 180 structures containing the (3,3-dimethyloxiran-2-yl)methyl fragment (3) as a basis for comparison and whose chemical shifts contradict the suggested structure (1).

Prediction of the structure of nobilisitine a using computed NMR chemical shifts

1H and 13C NMR computed chemical shifts are determined for eight diastereomers of the originally proposed structure of nobilisitine A, which has recently been shown to be incorrect. On the basis of comparison of the computed chemical shifts with those reported experimentally, we predict that the true structure of nobilisitine A is likely the diastereomer shown here or its enantiomer.

A systematic approach for the generation and verification of structural hypotheses

During the process of molecular structure elucidation the selection of the most probable structural hypothesis may be based on chemical shift prediction. The prediction is carried out using either empirical or quantum-mechanical (QM) methods. When QM methods are used, NMR prediction commonly utilizes the GIAO option of the DFT approximation. In this approach the structural hypotheses are expected to be investigated by scientist. In this article we hope to show that the most rational manner by which to create structural hypotheses is actually by the application of an expert system capable of deducing all potential structures consistent with the experimental spectral data and specifically using 2D NMR data. When an expert system is used the best structure(s) can be distinguished using chemical shift prediction, which is best performed either by an incremental or neural net algorithm. The time-consuming QM calculations can then be applied, if necessary, to one or more of the 'best' structures to confirm the suggested solution.

Computer-assisted methods for molecular structure elucidation: realizing a spectroscopist's dream

BACKGROUND

This article coincides with the 40 year anniversary of the first published works devoted to the creation of algorithms for computer-aided structure elucidation (CASE). The general principles on which CASE methods are based will be reviewed and the present state of the art in this field will be described using, as an example, the expert system Structure Elucidator.

RESULTS

The developers of CASE systems have been forced to overcome many obstacles hindering the development of a software application capable of drastically reducing the time and effort required to determine the structures of newly isolated organic compounds. Large complex molecules of up to 100 or more skeletal atoms with topological peculiarity can be quickly identified using the expert system Structure Elucidator based on spectral data. Logical analysis of 2D NMR data frequently allows for the detection of the presence of COSY and HMBC correlations of "nonstandard" length. Fuzzy structure generation provides a possibility to obtain the correct solution even in those cases when an unknown number of nonstandard correlations of unknown length are present in the spectra. The relative stereochemistry of big rigid molecules containing many stereocenters can be determined using the StrucEluc system and NOESY/ROESY 2D NMR data for this purpose.

CONCLUSION

The StrucEluc system continues to be developed in order to expand the general applicability, provide improved workflows, usability of the system and increased reliability of the results. It is expected that expert systems similar to that described in this paper will receive increasing acceptance in the next decade and will ultimately be integrated directly to analytical instruments for the purpose of organic analysis. Work in this direction is in progress. In spite of the fact that many difficulties have already been overcome to deliver on the spectroscopist's dream of "fully automated structure elucidation" there is still work to do. Nevertheless, as the efficiency of expert systems is enhanced the solution of increasingly complex structural problems will be achievable.