Enhancing NMR Prediction for Organic Compounds Using Molecular Dynamics

Dynamic Vertical Triplet Energies: Understanding and Predicting Triplet Energy Transfer

A computational approach for modeling and predicting triplet energy sensitization of organic molecules is described, which involves sampling the instantaneous, vertical energy gaps over molecular vibrational motions. This approach provides new theoretical support for the hot-band mechanism of energy transfer, in which the energy difference between donor and acceptor can be lessened by geometric distortions. We demonstrate excellent predictive performance against experimental triplet energies, with R2 = 0.97 and a mean absolute error (MAE) of 1.7 kcal/mol, for a collection of 24 small organic molecules, whereas a static, adiabatic description performs significantly worse (R2 = 0.51, MAE = 9.5 kcal/mol). Using this approach, it is possible to quantitatively predict the correct E/Z-isomerism of alkenes under energy transfer, for which adiabatic calculations predict the wrong outcome.

The anti-aromatic dianion and aromatic tetraanion of [18]annulene

π-Conjugated macrocycles behave differently from analogous linear chains because their electronic wavefunctions resemble a quantum particle on a ring, leading to aromaticity or anti-aromaticity. [18]Annulene, (CH)18, is the archetypal non-benzenoid aromatic hydrocarbon. Molecules with circuits of 4n + 2 π electrons, such as [18]annulene (n = 4), are aromatic, with enhanced stability and diatropic ring currents (magnetic shielding inside the ring), whereas those with 4n π electrons, such as the dianion of [18]annulene, are expected to be anti-aromatic and exhibit the opposite behaviour. Here we use 1H NMR spectroscopy to re-evaluate the structure of the [18]annulene dianion. We also show that it can be reduced further to an aromatic tetraanion, which has the same shape as the dianion. The crystal structure of the tetraanion lithium salt confirms its geometry and reveals a metallocene-like sandwich, with five Li+ cations intercalated between two [18]annulene tetraanions. We also report a heteroleptic sandwich, with [18]annulene and corannulene tetraanion decks.

Bispericyclic Ambimodal Dimerization of Pentafulvene: The Origin of Asynchronicity and Kinetic Selectivity of the Endo Transition State

The propensity of fulvenes to undergo dimerization has long been known, although the in-depth mechanism and electronic behavior during dimerization are still elusive. Herein, we made an attempt to gain insights into the reactivity of pentafulvene for Diels-Alder (DA) and [6 + 4]-cycloadditions via conventional and ambimodal routes. The result emphasizes that pentafulvene dimerization preferentially proceeds through a unique bifurcation mechanism where two DA pathways merge together to produce two degenerate [4 + 2]-cycloadducts from a single TS. Despite the [6 + 4]-cycloadduct being thermodynamically preferred, [4 + 2]-cycloaddition reactions are kinetically driven. Singlet biradicaloid is involved in through-space 6e- delocalization as a secondary orbital interaction that originates asynchronicity and stabilizes the bispericyclic transition state (TS). The transformation of various actively participating intrinsic bonding orbitals (IBOs) unambiguously forecasts the formation of multiple products from a single TS and rationalizes the mechanism of ambimodal reactions that are rather difficult to probe with other analyses. The changes in active IBOs clearly distinguish the conventional reactions from bifurcation reactions and can be employed to characterize and confirm the ambimodal mechanism. This report gains a crucial theoretical insight into the mechanism of bifurcation, the origin of asynchronicity, and electronic behavior in ambimodal TS, which will certainly be of enormous value for future studies.

Deconvolution and Analysis of the 1H NMR Spectra of Crude Reaction Mixtures

Nuclear magnetic resonance (NMR) spectroscopy is an important analytical technique in synthetic organic chemistry, but its integration into high-throughput experimentation workflows has been limited by the necessity of manually analyzing the NMR spectra of new chemical entities. Current efforts to automate the analysis of NMR spectra rely on comparisons to databases of reported spectra for known compounds and, therefore, are incompatible with the exploration of new chemical space. By reframing the NMR spectrum of a reaction mixture as a joint probability distribution, we have used Hamiltonian Monte Carlo Markov Chain and density functional theory to fit the predicted NMR spectra to those of crude reaction mixtures. This approach enables the deconvolution and analysis of the spectra of mixtures of compounds without relying on reported spectra. The utility of our approach to analyze crude reaction mixtures is demonstrated with the experimental spectra of reactions that generate a mixture of isomers, such as Wittig olefination and C-H functionalization reactions. The correct identification of compounds in a reaction mixture and their relative concentrations is achieved with a mean absolute error as low as 1%.

Structure of [18]Annulene Revisited: Challenges for Computing Benzenoid Systems

For cyclic conjugated structures, erratic computational results have been obtained with Hartree-Fock (HF) molecular orbital (MO) methods as well as density functional theory (DFT) with large HF-exchange contributions. In this work, the reasons for this unreliability are explored. Extensive computations on [18]annulene and related compounds highlight the pitfalls to be avoided and the due diligence required for such computational investigations. In particular, a careful examination of the MO singlet-stability eigenvalues is recommended. The appearance of negative eigenvalues is not (necessarily) problematic, but near-zero (positive or negative) eigenvalues can lead to dramatic errors in vibrational frequencies and related properties. DFT approaches with a lower HF admixture generally appear more robust in this regard for the description of benzenoid structures, although they may exaggerate the tendency toward planarity and C-C bond-equalization. For the iconic [18]annulene, the results support a nonplanar equilibrium structure. The density-fitted frozen natural orbital coupled-cluster singles and doubles with perturbative triples [DF-FNO CCSD(T)] method of electron correlation with an aug-pVQZ/aug-pVTZ basis set places the C2 global minimum 1.1 kcal mol-1 below the D6h stationary point.

Reaction dynamics as the missing puzzle piece: the origin of selectivity in oxazaborolidinium ion-catalysed reactions

The selectivity in a group of oxazaborolidinium ion-catalysed reactions between aldehyde and diazo compounds cannot be explained using transition state theory. VRAI-selectivity, developed to predict the outcome of dynamically controlled reactions, can account for both the chemo- and the stereo-selectivity in these reactions, which are controlled by reaction dynamics. Subtle modifications to the substrate or catalyst substituents alter the potential energy surface, leading to changes in predominant reaction pathways and altering the barriers to the major product when reaction dynamics are considered. In addition, this study suggests an explanation for the mysterious inversion of enantioselectivity resulting from the inclusion of an orthoiPrO group in the catalyst.

Metal-Free Arylation of Benzothiophenes at C4 by Activation as their Benzothiophene S-Oxides

Benzothiophenes, activated by oxidation to the corresponding S-oxides, undergo C-H/C-H-type coupling with phenols to give C4 arylation products. While an electron-withdrawing group at C3 of the benzothiophene is important, the process operates without a directing group and a metal catalyst, thus rendering it compatible with sensitive functionalities-e.g. halides and formyl groups. Quantum chemical calculations suggest a formal stepwise mechanism involving heterolytic cleavage of an aryloxysulfur species to give a π-complex of the corresponding benzothiophene and a phenoxonium cation. Subsequent addition of the phenoxonium cation to the C4 position of the benzothiophene is favored over the addition to C3; Fukui functions predict that the major regioisomer is formed at the more electron-rich position between C3 and C4. Varied selective manipulation of the benzothiophene products showcase the synthetic utility of the metal-free arylation process.

Synthesis of Bis(amino acids) Containing the Styryl-cyclobutane Core by Photosensitized [2+2]-Cross-cycloaddition of Allylidene-5(4H)-oxazolones

The irradiation of 2-aryl-4-(E-3'-aryl-allylidene)-5(4H)-oxazolones 1 with blue light (456 nm) in the presence of [Ru(bpy)₃](BF₄)₂ (bpy = 2,2'-bipyridine, 5% mol) gives the unstable cyclobutane-bis(oxazolones) 2 by [2+2]-photocycloaddition of two oxazolones 1. Each oxazolone contributes to the formation of 2 with a different C=C bond, one of them reacting through the exocyclic C=C bond, while the other does so through the styryl group. Treatment of unstable cyclobutanes 2 with NaOMe/MeOH produces the oxazolone ring opening reaction, affording stable styryl-cyclobutane bis(amino acids) 3. The reaction starts with formation of the T₁ excited state of the photosensitizer ³[Ru*(bpy)₃]²⁺, which reacts with S₀ of oxazolones 1 through energy transfer to give the oxazolone T₁ state ³(oxa*)-1, which is the reactive species and was characterized by transient absorption spectroscopy. Measurement of the half-life of ³(oxa*)-1 for 1a, 1b and 1d shows large values for 1a and 1b (10-12 μs), while that of 1d is shorter (726 ns). Density functional theory (DFT) modeling displays strong structural differences in the T₁ states of the three oxazolones. Moreover, study of the spin density of T₁ state ³(oxa*)-1 provides clues to understanding the different reactivity of 4-allylidene-oxazolones described here with respect to the previously reported 4-arylidene-oxazolones.

Improving the accuracy of 31P NMR chemical shift calculations by use of scaling methods

Calculation of ³¹P NMR chemical shifts for a series of tri- and tetracoordinate phosphorus compounds using several basis sets and density functional theory (DFT) functionals gave a modest fit to experimental chemical shifts, but an excellent linear fit when plotted against the experimental values. The resultant scaling methods were then applied to a variety of "large" compounds previously selected by Latypov et al. and a set of stereoisomeric and unusual compounds selected here. No one method was best for all structural types. For compounds that contain P-P bonds and P-C multiple bonds, the Latypov et al. method using the PBE0 functional was best (mean absolute deviation/root mean square deviation (MAD/RMSD) = 6.9/8.5 ppm and 6.6/8.2 ppm, respectively), but for the full set of compounds gave higher deviations (MAD/RMSD = 8.2/12.3 ppm), and failed by over 60 ppm for a three-membered phosphorus heterocycle. Use of the M06-2X functional for both the structural optimization and NMR chemical shift calculation was best overall for the compounds without P-C multiple bonds (MAD/RMSD = 5.4/7.1 ppm), but failed by 30-49 ppm for compounds having any P-C multiple-bond character. Failures of these magnitudes have not been reported previously for these widely used functionals. These failures were then used to screen a variety of recommended functionals, leading to better overall methods for calculation of these chemical shifts: optimization with the M06-2X functional and NMR calculation with the PBE0 or ωB97x-D functionals gave values for MAD/RMSD = 6.9/8.5 ppm and 6.8/9.1 ppm, respectively, over an experimental chemical shift range of -181 to 356 ppm. Due to the unexplained failures observed, we recommend use of more than one method when looking at novel structures.

Mechanistic Aspects on [3+2] Cycloaddition (32CA) Reactions of Azides to Nitroolefins: A Computational and Kinetic Study

[3+2] cycloadditions of nitroolefins have emerged as a selective and catalyst-free alternative for the synthesis of 1,2,3-triazoles from azides. We describe mechanistic studies into the cycloaddition/rearomatization reaction sequence. DFT calculations revealed a rate-limiting cycloaddition step proceeding via an asynchronous TS with high kinetic selectivity for the 1,5-triazole. Kinetic studies reveal a second-order rate law, and ¹³ C kinetic isotopic effects at natural abundance were measured with a significant normal effect at the conjugated olefinic centers of 1.0158 and 1.0216 at the α and β-carbons of β-nitrostyrene. Distortion/interaction-activation strain and energy decomposition analyses revealed that the major regioisomeric pathway benefits from an earlier and less-distorted TS, while intermolecular interaction terms dominate the preference for 1,5- over 1,4-cycloadducts. In addition, the major regioisomer also has more favorable electrostatic and dispersion terms. Additionally, while static DFT calculations suggest a concerted but highly asynchronous Ei-type HNO₂ elimination mechanism, quasiclassical direct-dynamics calculations reveal the existence of a dynamic intermediate.

Prediction of chemical shift in NMR: A review

Calculation of solution-state NMR parameters, including chemical shift values and scalar coupling constants, is often a crucial step for unambiguous structure assignment. Data-driven (sometimes called empirical) methods leverage databases of known parameter values to estimate parameters for unknown or novel molecules. This is in contrast to popular ab initio techniques that use detailed quantum computational chemistry calculations to arrive at parameter estimates. Data-driven methods have the potential to be considerably faster than ab inito techniques and have been the subject of renewed interest over the past decade with the rise of high-quality databases of NMR parameters and novel machine learning methods. Here, we review these methods, their strengths and pitfalls, and the databases they are built on.

Impact of solvent interactions on 1H and 13C chemical shifts investigated using DFT and a reference dataset recorded in CDCl3 and CCl4

1H and 13C chemical shifts of 35 small, rigid molecules were measured under standardized conditions in chloroform-d and in tetrachloromethane. The solvent change mainly affects carbon shifts of polar functional groups. This difference due to specific interactions with CDCl3 cannot be adequately reproduced by DFT calculations in implicit solvent. The new dataset provides an accurate basis for the validation and calibration of shift calculations, especially with respect to improved solvent models.

An initial investigation of accuracy required for the identification of small molecules in complex samples using quantum chemical calculated NMR chemical shifts

The majority of primary and secondary metabolites in nature have yet to be identified, representing a major challenge for metabolomics studies that currently require reference libraries from analyses of authentic compounds. Using currently available analytical methods, complete chemical characterization of metabolomes is infeasible for both technical and economic reasons. For example, unambiguous identification of metabolites is limited by the availability of authentic chemical standards, which, for the majority of molecules, do not exist. Computationally predicted or calculated data are a viable solution to expand the currently limited metabolite reference libraries, if such methods are shown to be sufficiently accurate. For example, determining nuclear magnetic resonance (NMR) spectroscopy spectra in silico has shown promise in the identification and delineation of metabolite structures. Many researchers have been taking advantage of density functional theory (DFT), a computationally inexpensive yet reputable method for the prediction of carbon and proton NMR spectra of metabolites. However, such methods are expected to have some error in predicted 13C and 1H NMR spectra with respect to experimentally measured values. This leads us to the question-what accuracy is required in predicted 13C and 1H NMR chemical shifts for confident metabolite identification? Using the set of 11,716 small molecules found in the Human Metabolome Database (HMDB), we simulated both experimental and theoretical NMR chemical shift databases. We investigated the level of accuracy required for identification of metabolites in simulated pure and impure samples by matching predicted chemical shifts to experimental data. We found 90% or more of molecules in simulated pure samples can be successfully identified when errors of 1H and 13C chemical shifts in water are below 0.6 and 7.1 ppm, respectively, and below 0.5 and 4.6 ppm in chloroform solvation, respectively. In simulated complex mixtures, as the complexity of the mixture increased, greater accuracy of the calculated chemical shifts was required, as expected. However, if the number of molecules in the mixture is known, e.g., when NMR is combined with MS and sample complexity is low, the likelihood of confident molecular identification increased by 90%.

Homologation of Electron-Rich Benzyl Bromide Derivatives via Diazo C-C Bond Insertion

The ability to manipulate C-C bonds for selective chemical transformations is challenging and represents a growing area of research. Here, we report a formal insertion of diazo compounds into the "unactivated" C-C bond of benzyl bromide derivatives catalyzed by a simple Lewis acid. The homologation reaction proceeds via the intermediacy of a phenonium ion, and the products contain benzylic quaternary centers and an alkyl bromide amenable to further derivatization. Computational analysis provides critical insight into the reaction mechanism, in particular the key selectivity-determining step.

Metabolite Structure Assignment Using In Silico NMR Techniques

A major challenge for metabolomic analysis is to obtain an unambiguous identification of the metabolites detected in a sample. Among metabolomics techniques, NMR spectroscopy is a sophisticated, powerful, and generally applicable spectroscopic tool that can be used to ascertain the correct structure of newly isolated biogenic molecules. However, accurate structure prediction using computational NMR techniques depends on how much of the relevant conformational space of a particular compound is considered. It is intrinsically challenging to calculate NMR chemical shifts using high-level DFT when the conformational space of a metabolite is extensive. In this work, we developed NMR chemical shift calculation protocols using a machine learning model in conjunction with standard DFT methods. The pipeline encompasses the following steps: (1) conformation generation using a force field (FF)-based method, (2) filtering the FF generated conformations using the ASE-ANI machine learning model, (3) clustering of the optimized conformations based on structural similarity to identify chemically unique conformations, (4) DFT structural optimization of the unique conformations, and (5) DFT NMR chemical shift calculation. This protocol can calculate the NMR chemical shifts of a set of molecules using any available combination of DFT theory, solvent model, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Our protocol reduces the overall computational time by 2 orders of magnitude over methods that optimize the conformations using fully ab initio methods, while still producing good agreement with experimental observations. The complete protocol is designed in such a manner that makes the computation of chemical shifts tractable for a large number of conformationally flexible metabolites.

Predicting 19 F NMR Chemical Shifts: A Combined Computational and Experimental Study of a Trypanosomal Oxidoreductase-Inhibitor Complex

The absence of fluorine from most biomolecules renders it an excellent probe for NMR spectroscopy to monitor inhibitor-protein interactions. However, predicting the binding mode of a fluorinated ligand from a chemical shift (or vice versa) has been challenging due to the high electron density of the fluorine atom. Nonetheless, reliable 19 F chemical-shift predictions to deduce ligand-binding modes hold great potential for in silico drug design. Herein, we present a systematic QM/MM study to predict the 19 F NMR chemical shifts of a covalently bound fluorinated inhibitor to the essential oxidoreductase tryparedoxin (Tpx) from African trypanosomes, the causative agent of African sleeping sickness. We include many protein-inhibitor conformations as well as monomeric and dimeric inhibitor-protein complexes, thus rendering it the largest computational study on chemical shifts of 19 F nuclei in a biological context to date. Our predicted shifts agree well with those obtained experimentally and pave the way for future work in this area.

One-bond 1 J(15 N─19 F) spin-spin coupling constants of cationic fluorinating reagents: Insights from DFT calculations

We have investigated, by means of density functional theory protocols, the one-bond ¹ J(¹⁵ N─¹⁹ F) spin-spin coupling constants in a series of fluorinating reagents, containing the N─F bond, recently studied experimentally. The results of the calculations show a very good linear relationship with the experimental values, even though only the M06-2X(PCM)/pcJ-2//B3LYP/6-311G(d,p) level affords a very low mean absolute error. The calculations allow to analyze the various molecular orbitals contributions to the J coupling and to rationalize the observed positive sign, corresponding to a negative sign of the reduced spin-pin coupling constant K(N─F). Moreover, of the four Ramsey contributions, only the diamagnetic spin orbit is negligible, whereas the paramagnetic spin orbit and spin dipole terms decrease the magnitude of the Fermi contact (FC) term by an amount that goes from a minimum of 35% up to more than 60% of the FC term itself. Several effects have been investigated, namely, the contribution of the long-range solvent reaction field, relativistic corrections, and conformational and vibrational effects.

Structure elucidation and absolute configuration of metabolites from the soil-derived fungus Dictyosporium digitatum using spectroscopic and computational methods

Following the discovery of a new class of compounds that inhibit the mucosa-associated lymphoid tissue lymphoma translocation 1 (MALT1) protease in a prior study, further chemical investigation of the Dictyosporium digitatum fungus resulted in the identification of 16 additional metabolites, including 12 undescribed compounds (1-12). The constitution and relative configuration of these new molecules were established by comprehensive NMR and HRMS analyses. Their absolute configurations were determined by employing Mosher's ester analysis and TDDFT ECD calculations. Two sesquiterpenes, dictyosporins A (1) and B (2), possess an undescribed eudesmen-type of structural scaffold. The ability of the isolated compounds to inhibit MALT1 proteolytic activity was evaluated, but none of them exhibited significant inhibition.

Computational NMR Spectroscopy of Ionic Liquids: [C4C1im]Cl/Water Mixtures

In this work, I have analyzed the structure of binary mixtures of 1-butyl-3-methylimidazolium chloride ionic liquid, [C₄C₁im]Cl, and water, using computational NMR spectroscopy. The structure of the complex fluid phase, where the ionic and hydrophobic nature of ionic liquids is further complicated by the addition of water, is first generated by classical Molecular Dynamics (MD) and then validated by calculating the NMR properties with DFT at the ONIOM(B3LYP/cc-pVTZ//B3LYP/3-21G) on clusters extracted during the MD trajectories. Three ionic liquid/water mixtures have been considered with the [C₄C₁im]Cl mole fraction of 1.00, 0.50, and 0.01, that is the pure ionic liquid [C₄C₁im]Cl, the equimolar [C₄C₁im]Cl/water mixture, and a diluted solution of [C₄C₁im]Cl in water. A good agreement is obtained with published experimental data that, at the same time, validates the structural features obtained from the MD and the force field used, and provides an example of the power of NMR spectroscopy applied to complex fluid phases.

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

An Akaike Information Criterion (AIC) procedure (CASE-3D) has been successfully applied to the NMR based configurational assignment of reported hyacinthacines (1-3,5-8), recently target of configurational analysis using the popular DP4+ methodology. The present analysis makes use of reported ¹ H and ¹³ C shifts and, in some particular cases, a few ³ J_HH couplings. The difficulty in proper computational prediction of relative energies, in molecules capable of inter-molecular hydrogen bonding, introduces large errors in the prediction of conformationally averaged NMR properties in methods based on Boltzmann averaging such as DP4 or DP4+. In contrast CASE-3D conformational amplitudes are free parameters in the model. Here we show that the CASE-3D conformational model selection strategy, when combined with a larger energy cutoff in the molecular-modelling conformational exploration, was sufficient to correctly assign the relative configuration in five of seven cases. Introduction of more information, either by supplementing ¹ H and ¹³ C data with a few J-couplings, or using a cutoff based on computed DFT energies for the definition of the conformational ensembles, allowed the safe assignment of configuration for all compounds.

Rapid prediction of NMR spectral properties with quantified uncertainty

Accurate calculation of specific spectral properties for NMR is an important step for molecular structure elucidation. Here we report the development of a novel machine learning technique for accurately predicting chemical shifts of both \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${^1\mathrm{H}}$$\end{document}1H   and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${^{13}\mathrm{C}}$$\end{document}13C nuclei which exceeds DFT-accessible accuracy for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${^{13}\mathrm{C}}$$\end{document}13C and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${^1\mathrm{H}}$$\end{document}1H for a subset of nuclei, while being orders of magnitude more performant. Our method produces estimates of uncertainty, allowing for robust and confident predictions, and suggests future avenues for improved performance.

The role of computer-assisted structure elucidation (CASE) programs in the structure elucidation of complex natural products

Computer-assisted structure elucidation can help to determine the structures of complex natural products while minimizing the risk of structure errors.

An automated framework for NMR chemical shift calculations of small organic molecules

When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typically depended upon to build libraries experimentally. Considering complex biological samples, such as blood and soil, the entirety of NMR spectra required for all possible compounds would be infeasible to ascertain due to limitations of available standards and experimental processing time. As an alternative, we introduce the in silico Chemical Library Engine (ISiCLE) NMR chemical shift module to accurately and automatically calculate NMR chemical shifts of small organic molecules through use of quantum chemical calculations. ISiCLE performs density functional theory (DFT)-based calculations for predicting chemical properties—specifically NMR chemical shifts in this manuscript—via the open source, high-performance computational chemistry software, NWChem. ISiCLE calculates the NMR chemical shifts of sets of molecules using any available combination of DFT method, solvent, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Calculated NMR chemical shifts are provided to the user for each molecule, along with comparisons with respect to a number of metrics commonly used in the literature. Here, we demonstrate ISiCLE using a set of 312 molecules, ranging in size up to 90 carbon atoms. For each, calculation of NMR chemical shifts have been performed with 8 different levels of DFT theory, and with solvation effects using the implicit solvent Conductor-like Screening Model. The DFT method dependence of the calculated chemical shifts have been systematically investigated through benchmarking and subsequently compared to experimental data available in the literature. Furthermore, ISiCLE has been applied to a set of 80 methylcyclohexane conformers, combined via Boltzmann weighting and compared to experimental values. We demonstrate that our protocol shows promise in the automation of chemical shift calculations and, ultimately, the expansion of chemical shift libraries.

Method Calibration or Data Fitting?

We investigate by explicit parameter optimization to what extent basis sets of polarized double-ζ quality can introduce compensating errors in five different density functional methods. It is shown that minor changes in the contraction coefficients of the valence functions in the basis sets can have a significant impact and allow different density functional methods to achieve very similar performances. This holds for nuclear magnetic shielding constants and for isomerization energies, barrier heights, and noncovalent interactions. It is furthermore shown that errors due to neglect of vibrational and solvent effects can be absorbed in the combined method and basis set errors. These findings hold for data sets consisting of 50-150 data points. This raises the question of whether the common practice of identifying combinations of density functional methods and basis sets that have a good performance against a selected set of reference data should be considered as data fitting in the combined parameter space spanned by the method and basis set.

Influence of Solvent Representation on Nuclear Shielding Calculations of Protonation States of Small Biological Molecules

In this study, we assess the influence of solvation on the accuracy and reliability of isotropic nuclear magnetic shielding calculations for amino acids in comparison to experimental data. We focus particularly on the performance of solvation methods for different protonation states, as biological molecules occur almost exclusively in aqueous solution and are subject to protonation with pH. We identify significant shortcomings of current implicit solvent models and present a hybrid solvation approach that improves agreement with experimental data by taking into account the presence of direct interactions between amino acid protonation state and water molecules.

Polyacetylene: Myth and Reality

Polyacetylene, the simplest and oldest of potentially conducting polymers, has never been made in a form that permits rigorous determination of its structure. Trans polyacetylene in its fully extended form will have a potential energy surface with two equivalent minima. It has been assumed that this results in bond length alternation. It is, rather, very likely that the zero-point energy is above the Peierls barrier. The experimental studies that purport to show bond alternation are reviewed and shown to be compromised by serious experimental inconsistencies or by the presence, for which there is considerable evidence, of finite chain polyenes. In this view, addition of dopants results in conductivity by facilitation of charge transport between finite polyenes. The double minimum potential that necessarily occurs for polyacetylene, if viewed as the result of elongation of finite chains, originates from admixture of the 1¹A_g ground electronic state with the 2¹A_g excited electronic singlet state. This excitation is diradical (two electron) in character. The polyacetylene limit is an equal admixture of these two ¹A_g states making theory intractable for long chains. A method is outlined for preparation of high molecular weight polyacetylene with fully extended chains that are prevented from reacting with neighboring chains.

Fully Automated Quantum-Chemistry-Based Computation of Spin-Spin-Coupled Nuclear Magnetic Resonance Spectra

We present a composite procedure for the quantum‐chemical computation of spin–spin‐coupled ¹H NMR spectra for general, flexible molecules in solution that is based on four main steps, namely conformer/rotamer ensemble (CRE) generation by the fast tight‐binding method GFN‐xTB and a newly developed search algorithm, computation of the relative free energies and NMR parameters, and solving the spin Hamiltonian. In this way the NMR‐specific nuclear permutation problem is solved, and the correct spin symmetries are obtained. Energies, shielding constants, and spin–spin couplings are computed at state‐of‐the‐art DFT levels with continuum solvation. A few (in)organic and transition‐metal complexes are presented, and very good, unprecedented agreement between the theoretical and experimental spectra was achieved. The approach is routinely applicable to systems with up to 100–150 atoms and may open new avenues for the detailed (conformational) structure elucidation of, for example, natural products or drug molecules.

Improved Quantum Chemical NMR Chemical Shift Prediction of Metabolites in Aqueous Solution toward the Validation of Unknowns

A quantum-chemistry based protocol, termed MOSS-DFT, is presented for the prediction of ¹³C and ¹H NMR chemical shifts of a wide range of organic molecules in aqueous solution, including metabolites. Molecular motif-specific linear scaling parameters are reported for five different density functional theory (DFT) methods (B97-2/pcS-1, B97-2/pcS-2, B97-2/pcS-3, B3LYP/pcS-2, and BLYP/pcS-2), which were applied to a large set of 176 metabolite molecules. The chemical shift root-mean-square deviations (RMSD) for the best method, B97-2/pcS-3, are 1.93 and 0.154 ppm for ¹³C and ¹H chemical shifts, respectively. Excellent results have been obtained for chemical shifts of methyl and aromatic ¹³C and ¹H that are not directly bonded to a heteroatom (O, N, S, or P) with RMSD values of 1.15/0.079 and 1.31/0.118 ppm, respectively. This study not only demonstrates how NMR chemical shift in aqueous environment can be improved over the commonly used global linear scaling approach, but also allows for motif-specific error estimates, which are useful for an improved chemical shift-based verification of metabolite candidates of metabolomics samples containing unknown components.

State of the art and perspectives in the application of quantum chemical prediction of 1 H and 13 C chemical shifts and scalar couplings for structural elucidation of organic compounds

Quantum mechanical prediction of chemical shifts and scalar couplings involving ¹ H and ¹³ C nuclei is now a popular tool in structural elucidation of organic compounds. Here, we summarize the current state of the art and present to the reader present limitations and problems, mostly related to treatment of conformational flexibility, as well as future perspectives and potential applications in the field.