When not to rely on Boltzmann populations. Automated CASE-3D structure elucidation of hyacinthacines through chemical shift differences

Anisotropic NMR data acquisition with a prototype 400 MHz cryogen-free NMR spectrometer

High-temperature superconducting (HTS) materials have recently been incorporated into the construction of HTS cryogen-free magnets for nuclear magnetic resonance (NMR) spectroscopy. These HTS NMR spectrometers do not require liquid cryogens, thereby providing significant cost savings and facilitating easy integration into chemistry laboratories. However, the optimal performance of these HTS magnets against standard cryogen NMR magnets must be evaluated, especially with demanding modern NMR applications such as NMR in anisotropic media. The stability of the HTS magnets over time and their performance with complex pulse sequence experiments are the main unknown factors of this new technology. In this study, we evaluate the utility of our prototype 400 MHz cryogen-free power-driven HTS NMR spectrometer, installed in the fumehood of a chemistry laboratory, for stereochemical analysis of three commercial natural products (artemisinin, artemether, and dihydroartemisinin) via measurement of anisotropic NMR data, in particular, residual dipolar couplings. The accuracy of measurement of the anisotropic NMR data with the HTS magnet spectrometer is evaluated through the CASE-3D fitting protocol, as implemented in the Mestrenova-StereoFitter software program.

Phomactinine, the First Nitrogen-Bearing Phomactin, Produced by Biatriospora sp. CBMAI 1333

Metabolomics analyses and improvement of growth conditions were applied toward diversification of phomactin terpenoids by the fungus Biatriospora sp. CBMAI 1333. Visualization of molecular networking results on Gephi assisted the observation of phomactin diversification and guided the isolation of new phomactin variants by applying a modified version of chemometrics based on a fractional factorial design. Consequentially, the first nitrogen-bearing phomactin, phomactinine (1), with a new rearranged carbon skeleton, was isolated and identified. The strategy combining metabolomics and chemometrics can be extended to include bioassay potency, structure novelty, and metabolic diversification connected or not to genomic analyses.

Residual Dipolar Coupling Based Conformational Analysis Allows the Configurational Assessment of Steroids with up to Eight Stereocenters

Residual dipolar couplings (RDCs) induced by anisotropic media have been proved as a powerful tool for the structure elucidation of organic molecules in solution in nuclear magnetic resonance (NMR) based analysis. The value of dipolar couplings to solve complex conformational and configurational problems represents indeed an appealing analytical tool for the pharmaceutical industry particularly focusing on the stereochemistry characterization of NCEs since the early phase of the drug development process. In our work, RDCs were used for the conformational and configurational study of synthetic steroids with multiple stereocenters - prednisone and beclomethasone dipropionate (BDP) -. For both molecules the correct relative configuration was identified among all the possible diastereoisomers (32 and 128 respectively) arising from the compounds stereogenic carbons. Only for prednisone the use of additional experimental data (i. e. rOes) was necessary to resolve the right stereochemical structure.

Reconsideration of the Structures of Stemara-13(14)-en-18-ol and Related Diterpene Natural Products: Vinylic Hydrogen Chemical Shifts Are Key

The reported synthesis of stemara-13(14)-en-18-ol, which revealed that the structure of this natural product was misassigned, prompted an investigation using density functional theory methods into the structural reassignment of this natural product and related diterpenoids extracted from Calceolaria plants. ¹H and ¹³C chemical shift predictions led to the reassignment of relative configuration, and in one case the carbon skeleton, of several diterpenoids from Calceolaria. In many of these cases, the chemical shift of the vinylic hydrogen was found to be diagnostic.

NMR-Based Configurational Assignments of Natural Products: How Floating Chirality Distance Geometry Calculations Simplify Gambling with 2N-1 Diastereomers

Using NMR data, the assignment of the correct 3D configuration and conformation to unknown natural products is of pivotal importance in pharmaceutical and medicinal chemistry. In this report, we quantify the probability of configurational assignments to judge the quality of structural elucidations using Bayesian inference in combination with floating-chirality distance geometry simulations. Based on reference-free NOE/ROE data, residual dipolar couplings (RDCs), and residual quadrupolar couplings (RQCs) in various combinations, we demonstrate how the relative configurations of three natural compounds, namely, jatrohemiketal (1), artemisinin (2), and Taxol (3), can be unambiguously established without the necessity to carry out time-consuming DFT-based configurational and conformational analyses. Our results quantitatively describe how reliably molecular geometries can be inferred from experimental NMR data, thereby unequivocally unveiling remaining assignment ambiguities. The methodology presented here will dramatically reduce the risk of incorrect structural assignments based on the overinterpretation of incomplete data and DFT-based structure models in chemistry.

Weizhouochrones: Gorgonian-Derived Symmetric Dimers and Their Structure Elucidation Using Anisotropic NMR Combined with DP4+ Probability and CASE-3D

Natural product dimers have intriguing structural features and often have remarkable pharmacological activities. We report here two uncommon marine gorgonian-derived symmetric dimers, weizhouochrones A (1) and B (2), with indenone-derived monomers, that were isolated from the coral Anthogorgia ochracea collected from the South China Sea. These dimers are difficult targets for structure elucidation that solely relies upon conventional NMR data such as NOEs and J-couplings. Here, to explore the application of emerging methods on the structure elucidation of challenging molecules, we explored a number of different anisotropic and computational NMR approaches. The measurements of anisotropic NMR parameters of weizhouochrone A, including residual dipolar couplings (RDCs) and residual chemical shift anisotropy (RCSA), allowed us to successfully determine the planar structure and its relative configuration. This result was corroborated by a computational NMR analysis based on DP4+ probability and computer-assisted 3D structure elucidation (CASE-3D).

Statistical evaluation of simulated NMR data of flexible molecules

A new probability score-named χ-probability-is introduced for evaluating the fit of mixed NMR datasets to calculate molecular model ensembles, in order to answer challenging structural questions such as the determination of stereochemical configurations. Similar to the DP4 parameter, the χ-probability is based on Bayes theorem and expresses the probability that an experimental NMR dataset fits to a given individual within a finite set of candidate structures or configurations. Here, the χ-probability is applied to single out the correct configuration in four example cases, with increasing complexity and conformational mobility. The NMR data (which include RDCs, NOE distances and ³J couplings) are calculated from MDOC (Molecular Dynamics with Orientational Constraints) trajectories and are investigated against experimentally measured data. It is demonstrated that this approach singles out the correct stereochemical configuration with probabilities more than 98%, even for highly mobile molecules. In more demanding cases, a decisive χ-probability test requires that the datasets include high-quality NOE distances in addition to RDC values.

Bayesian Inference Applied to NMR-Based Configurational Assignments by Floating Chirality Distance Geometry Calculations

Using NMR data, the assignment of the correct 3D configuration and conformation to unknown natural products is of pivotal importance in pharmaceutical and medicinal chemistry. In this report, we quantify the quality and probability of structural elucidations using Bayesian inference in combination with floating chirality distance geometry simulations. Here, we will discuss the configurational analysis of three complex natural products including isopinocampheol (1), plakilactone H (2), and iodocallophycoic acid A (3) using NMR restraints of various types and in different combinations (residual dipolar couplings (RDCs) and NOE-derived distances). Our results quantitatively demonstrate how reliably molecular geometries can be inferred from experimental NMR data, unequivocally unveiling remaining assignment ambiguities. The methodology presented here can dramatically reduce the risk of incorrect structural assignments based on the overinterpretation of incomplete data in chemistry.

NMR-Based Configurational Assignments of Natural Products: Gibbs Sampling and Bayesian Inference Using Floating Chirality Distance Geometry Calculations

Floating chirality restrained distance geometry (fc-rDG) calculations are used to directly evolve structures from NMR data such as NOE-derived intramolecular distances or anisotropic residual dipolar couplings (RDCs). In contrast to evaluating pre-calculated structures against NMR restraints, multiple configurations (diastereomers) and conformations are generated automatically within the experimental limits. In this report, we show that the "unphysical" rDG pseudo energies defined from NMR violations bear statistical significance, which allows assigning probabilities to configurational assignments made that are fully compatible with the method of Bayesian inference. These "diastereomeric differentiabilities" then even become almost independent of the actual values of the force constants used to model the restraints originating from NOE or RDC data.

Computational Structural Revision of a 4-Hydroxy-3-(1'-angeloyloxy-2',3'-epoxy-3'-methyl)butylacetophenone Compound from Ageratina grandifolia

The structure of the reported compound 4-hydroxy-3-((S)-1'-angeloyloxy-(R)-2',3'-epoxy-3'-methyl)butylacetophenone (1), isolated from Ageratina grandifolia, has been revised through the use of DFT computational predictions. Re-examination of the reported experimental and DFT computed chemical shifts has led to the proposal of a chromane skeleton rather than the original epoxide derivative. Empirical predictions of the ¹³C and ¹H NMR shifts showed a much better fit for the chromane structure than for the epoxide. The relative configuration of the molecule was established using CASE-3D methodology on the basis of new DFT chemical shielding and J-coupling predictions, allowing the proposal of a new rel-2,2-dimethyl-3R-hydroxy-4S-(1-angeloyloxy)chromane structure (2) for the isolated compound. However, DFT prediction of the optical rotation for the CASE-3D selected configuration/conformations did not provide a conclusive answer for the absolute configuration.

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.

Configurational Analysis by Residual Dipolar Couplings: Critical Assessment of "Structural Noise" from Thermal Vibrations

The certainty of configurational assignments of natural products based on anisotropic NMR parameters, such as residual dipolar couplings (RDCs), must be amended by estimates on structural noise emerging from thermal vibrations. We show that vibrational analysis significantly affects the error margins with which RDCs can be back-calculated from molecular models, and the implications of thermal motions on the differentiability of diastereomers are derived.

NMR Calculations with Quantum Methods: Development of New Tools for Structural Elucidation and Beyond

Structural elucidation is an important and challenging stage in the discovery of new organic molecules. Single-crystal X-ray analysis provides the most unquestionable results, though in practice the availability of suitable crystals limits its broad use. On the other hand, NMR spectroscopy has become the leading and universal technique to accomplish the task. Despite continuous advances in the field, the misinterpretation of NMR data is commonplace, evidenced by the large number of erroneous structures being published in top journals. Quantum calculations of NMR chemical shifts and scalar coupling constants emerged as ideal complements to facilitate the elucidation process when experimental NMR data is inconclusive. Since seminal reports demonstrated that affordable DFT methods provide NMR predictions accurate enough to differentiate among closely related isomers, the discipline has experienced substantial growth. The impact has been felt in different areas, and nowadays the results of such calculations are routinely seen in high impact literature.This Account describes our investigations in the field of quantum NMR calculations, focusing on the development of tools for structural elucidation and practical applications. We pioneered the use of artificial intelligence methods in the development of novel strategies of structural validation. Our first generation of trained artificial neural networks (ANNs) showed excellent ability to identify mistakes at the atom connectivity level, whereas the use of multidimensional pattern recognition pushed the performance to the stereochemical limit. In a conceptually different approach, we developed DP4+, an updated version of the DP4 probability used to determine the most likely structure among two or more candidates when one set of experimental data is available. Increasing the level of theory in NMR calculations and including unscaled data in the formalism improved the performance of the method, further validated to settle the configuration of challenging motifs such as spiroepoxides or Mosher's derivatives. One of the limitations of DP4+ is related to the relatively large computational cost involved in obtaining DFT-optimized geometries, which led to the development of a fast variant including the valuable information provided by coupling constants (J-DP4 method).These tools were explored to suggest the most probable structure of controversial natural or unnatural products originally misassigned, with some predictions further validated by synthesis (as in the case of pseudorubriflordilactone B). The possibility of predicting the structure of a natural product without requiring authentic sample was investigated in collaboration with Prof. Pilli (UNICAMP, Brazil) in the computer-guided total synthesis and stereochemical revisions of several natural products. Despite these advances, there remain considerable challenges, such as the case of configurational assessment of polar systems featuring multiple intramolecular hydrogen bonding interactions because of the poor energy predictions provided by most DFT methods. In our latest work, we tackle this problem by averaging the results provided by randomly generated ensembles, paving the way for a new paradigm in quantum NMR-assisted structural elucidation.

The Advanced Floating Chirality Distance Geometry Approach-How Anisotropic NMR Parameters Can Support the Determination of the Relative Configuration of Natural Products

The configurational analysis of complex natural products by NMR spectroscopy is still a challenging task. The assignment of the relative configuration is usually carried out by analysis of interproton distances from NOESY or ROESY spectra (qualitative or quantitative) and scalar (J) couplings. About 15 years ago, residual dipolar couplings (RDCs) were introduced as a tool for the configurational determination of small organic molecules. In contrast to NOEs/ROEs which are local parameters (distances up to 400 pm can be detected for small organic molecules), RDCs are global parameters which allow to obtain structural information also from long-range relationships. RDCs have the disadvantage that the sample needs a setup in an alignment medium in order to obtain the required anisotropic environment. Here, we will discuss the configurational analysis of five complex natural products: axinellamine A (1), tetrabromostyloguanidine (2), 3,7-epi-massadine chloride (3), tubocurarine (4), and vincristine (5). Compounds 1-3 are marine natural products whereas 4 and 5 are from terrestrial sources. The chosen examples will carefully work out the limitations of NOEs/ROEs in the configurational analysis of natural products and will also provide an outlook on the information obtained from RDCs.