Do Double-Hybrid Exchange-Correlation Functionals Provide Accurate Chemical Shifts? A Benchmark Assessment for Proton NMR

Predicting 35-Cl electric field gradient tensors in crystalline solids using cluster and fragment-corrected planewave density functional theory

Planewave-corrected methods have proven effective for accurately modeling nuclear magnetic resonance (NMR) parameters in crystalline systems. Recent work extended the application of planewave-corrected calculations beyond the second row, predicting EFG tensor parameters for 35Cl using a simple molecular correction to projector augmented-wave (PAW) density functional theory (DFT). Here we extend this work using fragment and cluster-based calculations coupled with polarizable continuum (PCM) methods to improve further the accuracy of planewave-corrected 35Cl EFG tensor calculations. Benchmark data from a test set comprised of 105 individual 35Cl EFG tensor principal components for chlorine-containing molecular crystals and crystalline chloride salts shows fragment-corrected planewave calculations using the PBE0 hybrid density functional improve the accuracy of predicted EFG tensor components by 30 % relative to traditional planewave calculations. We compare the influence of different geometry optimization methods and density functionals on the accuracy of predicted 35Cl EFG tensor parameters. Four cases of spectral assignment are presented to demonstrate the utility of improving the accuracy of predicted 35Cl EFG tensor parameters.

Using atomic clustering based on structural and electronic descriptors that consider surrounding environment to evaluate local properties of DFT functionals

We developed a method for evaluating the accuracies of the local properties of DFT functionals in detail using a clustering method based on machine learning and structural/electronic descriptors. We generated 36 clusters consistent with human intuition using 30,436 carbon atoms from the QM9 dataset. The results were used to evaluate 13C NMR chemical shifts calculated using 84 DFT functionals. Carbon atoms were grouped based on their similar environments, reducing errors within these groups. This enables more accurate assessment of the accuracy using a specific DFT functional. Therefore, the present atomic clustering provides more detailed insight into accuracy verification.

An Isolable THF-Coordinated Dialkylgermanone

A stable dialkylgermanone was generated by mixing a solid of the corresponding dialkylgermylene and gaseous N2O. While the dialkylgermanone is marginally persistent in solution and gradually converts to its head-to-tail dimer at room temperature, the addition of THF to the dialkylgermanone provided an isolable THF-coordinated dialkylgermanone. The THF-coordinated dialkylgermanone reacts with H2O, THF, and B(C6F5)3 similar to the corresponding base-free two-coordinate dialkylsilanone. The dialkylgermanone undergoes deoxygenation in the presence of triphenylphosphine to provide the corresponding germylene and olefination upon treatment with phosphaylide Ph3PCHPh to afford the corresponding Ge=C bond compound (germa-Wittig reaction).

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%.

Hyperhenrones: Prenylated α-pyrones with anti-inflammatory activity from Hypericum henryi

Fourteen previously undescribed α-pyrone derivatives (1-14) together with four known analogs (15-18) were isolated from a traditional Chinese medicinal plant Hypericum henryi. Compounds (+)/(-)-1, 2, and 3 share a rare 6/6/4/6/6 polycyclic skeleton. Compound 14 was the first example of a 7,7-dimethyl-pyran-4-one moiety. Their structures were elucidated using comprehensive spectroscopic analyses and electronic circular dichroism calculations. The anti-inflammatory activities of 1-18 were screened in lipopolysaccharide-induced RAW264.7 cells. Among them, compounds 14, (+)-18, and (-)-18 exhibited inhibitory effects against nitric oxide production in LPS-induced RAW264.7 cells. Additionally, compound 14 suppressed the expression of cyclooxygenase-2 and inducible nitric oxide synthase in LPS-induced RAW264.7 cells. Furthermore, preliminary mechanism studies indicated that compound 14 suppressed the phosphorylation and degradation of the inhibitor of NF-κB, and this led to the inhibition of NF-κB activation.

Study of the electronic effect and quantitative spectra predictions of o-methoxyaniline-terminated monoazonaphthols: a combined experimental and DFT study

A combined experimental and density functional theory (DFT) study on the UV-Vis spectra of o-methoxyaniline-terminated mono azo dyes was conducted. By applying time-dependent-DFT calculations, details of excitation processes were determined and visualization by hole-electron analysis was undertaken. Fragment-divided analysis revealed the contributions of different parts of the structures for the UV-Vis spectra, that richer/poorer electron density on aromatic rings lead to greater/less maximum absorption wavelengths (λmax) and larger/smaller half peak width (W1/2). Combining theoretical prediction with experimental verification, we answered the question of how the electronegativities of substituents affected the electron densities and how it affected the spectra. In addition, a linear model connecting the λmax and W1/2 to the chemical shifts obtained by NMR spectroscopy was constructed, which laid the foundation for construction of a spectral library.

Computation of CCSD(T)-Quality NMR Chemical Shifts via Δ-Machine Learning from DFT

NMR spectroscopy undoubtedly plays a central role in determining molecular structures across different chemical disciplines, and the accurate computational prediction of NMR parameters is highly desirable. In this work, a new Δ-machine learning approach is presented to correct DFT-computed NMR chemical shifts using input features from the calculation and in addition highly accurate reference data at the CCSD(T)/pcSseg-2 level of theory with a basis set extrapolation scheme. The model is trained on a data set containing 1000 optimized and geometrically distorted structures of small organic molecules comprising most elements of the first three periods and containing data for 7090 ¹H and 4230 ¹³C NMR chemical shifts. Applied to the PBE0/pcSseg-2 method, the mean absolute deviation (MAD) on the internal NMR shift test set is reduced by 81% for ¹H and 92% for ¹³C at virtually no additional computational cost. For 12 different DFT functional and basis set combinations, the MAD of the ML-corrected NMR shifts ranges from 0.021 to 0.039 ppm (¹H) and from 0.38 to 1.07 ppm (¹³C). Importantly, the new method consistently outperforms the simple and widely used linear regression correction technique. This behavior is reproduced on three different external benchmark sets, confirming the generality and robustness of the correction scheme, which can easily be applied in DFT-based spectral simulations.

An in-silico NMR laboratory for nuclear magnetic shieldings computed via finite fields: Exploring nucleus-specific renormalizations of MP2 and MP3

We developed and implemented a method-independent, fully numerical, finite difference approach to calculating nuclear magnetic resonance shieldings, using gauge-including atomic orbitals. The resulting capability can be used to explore non-standard methods, given only the energy as a function of finite-applied magnetic fields and nuclear spins. For example, standard second-order Møller-Plesset theory (MP2) has well-known efficacy for 1H and 13C shieldings and known limitations for other nuclei such as 15N and 17O. It is, therefore, interesting to seek methods that offer good accuracy for 15N and 17O shieldings without greatly increased compute costs, as well as exploring whether such methods can further improve 1H and 13C shieldings. Using a small molecule test set of 28 species, we assessed two alternatives: κ regularized MP2 (κ-MP2), which provides energy-dependent damping of large amplitudes, and MP2.X, which includes a variable fraction, X, of third-order correlation (MP3). The aug-cc-pVTZ basis was used, and coupled cluster with singles and doubles and perturbative triples [CCSD(T)] results were taken as reference values. Our κ-MP2 results reveal significant improvements over MP2 for 13C and 15N, with the optimal κ value being element-specific. κ-MP2 with κ = 2 offers a 30% rms error reduction over MP2. For 15N, κ-MP2 with κ = 1.1 provides a 90% error reduction vs MP2 and a 60% error reduction vs CCSD. On the other hand, MP2.X with a scaling factor of 0.6 outperformed CCSD for all heavy nuclei. These results can be understood as providing renormalization of doubles amplitudes to partially account for neglected triple and higher substitutions and offer promising opportunities for future applications.

Intramolecular O···H Hydrogen Bonding of Salicylic Acid: Further Insights from O 1s XPS and 1H NMR Spectra Using DFT Calculations

Intramolecular hydrogen bonding (HB) is a complex phenomenon that extends beyond a simple valence event, affecting the core electrons of a molecule. Salicylic acid (SA) and its conformers provide an excellent model compound for studying intramolecular HB as the proton donor (H) and acceptor (O) can be toggled by rotating the C-O and C-C bonds to form up to seven potential conformers through various HB. In this study, we computationally investigated intramolecular interactions in SA conformers with and without such HB, by examining their calculated O 1s core electron-binding energy (CEBE) and ¹H NMR chemical shifts validated using recent measurements. The quantum mechanically stable SA conformers are fully defined by three rotatable bonds in the compound, which are abstracted as SA(η₁η₂η₃) digital structures, where η_i = 0 if the η_i angles match the most stable SA conformer (000) and η_i = 1 otherwise. Our findings suggest that the stability is dominated by the appearance of the intergroup intramolecular HB of H_p···O (where O is in the carboxylic acid functional group and H_p is the phenolic proton in -OH_p), and η₃ serves as a switch of such HB. As a result, the (η₁η₂0) SA conformers containing such H_p···O HB are more stable than other SA conformers (η₁η₂1) without such the H_p···O HB. The present density functional theory calculations reveal that this H_p···O HB results in splitting of the O 1s CEBEs of two hydroxyl groups (-OH) by up to 1 eV and deshielding the H_p proton ¹H NMR (δH_p) up to 11.68 ppm for the (η₁η₂0) conformers. Without such H_p···O HB, the O 1s XPS binding energies of two -OH groups will be closely located in the same band, and the ¹H NMR chemical shift of the H_p atom will be as small as an 4.09 ppm SA conformer [SA-G(101)]. The present study indicates that the O 1s CEBE splitting between two -OH groups serves as an indicator of the presence of the H_p···O HB in SA conformers, which is also supported by the ¹H NMR results.

Do Models beyond Hybrid Density Functionals Increase the Agreement with Experiment for Predicted NMR Chemical Shifts or Electric Field Gradient Tensors in Organic Solids?

Ab initio predictions of chemical shifts and electric field gradient (EFG) tensor components are frequently used to help interpret solid-state nuclear magnetic resonance (NMR) experiments. Typically, these predictions employ density functional theory (DFT) with generalized gradient approximation (GGA) functionals, though hybrid functionals have been shown to improve accuracy relative to experiment. Here, the performance of a dozen models beyond the GGA approximation are examined for the prediction of solid-state NMR observables, including meta-GGA, hybrid, and double-hybrid density functionals and second-order Møller-Plesset perturbation theory (MP2). These models are tested on organic molecular crystal data sets containing 169 experimental ¹³C and ¹⁵N chemical shifts and 114 ¹⁷O and ¹⁴N EFG tensor components. To make these calculations affordable, gauge-including projector augmented wave (GIPAW) Perdew-Burke-Ernzerhof (PBE) calculations with periodic boundary conditions are combined with a local intramolecular correction computed at the higher level of theory. Within the context of typical NMR property calculations performed on a static, DFT-optimized crystal structure, the benchmarking finds that the double-hybrid DFT functionals produce errors versus experiment that are no smaller than those of hybrid functionals in the best cases, and they can be larger. MP2 errors versus experiment are even bigger. Overall, no practical advantages are found for using any of the tested double-hybrid functionals or MP2 to predict experimental solid-state NMR chemical shifts and EFG tensor components for routine organic crystals, especially given the higher computational cost of those methods. This finding likely reflects error cancellation benefiting the hybrid functionals. Improving the accuracy of the predicted chemical shifts and EFG tensors relative to experiment would probably require more robust treatments of the crystal structures, their dynamics, and other factors.

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.

Antifungal polyketides from the marine-derived fungus Nigrospora sp. MG36-1

Three new polyketides, a griseofulvin derivative 1, a hydroanthraquinone derivative 8 and a pyranolactone derivative 10, together with eight known compounds (2-7, 9 and 11), were isolated from the marine-derived fungus Nigrospora sp. MG36-1. The structures of the three new compounds were unambiguously determined by nuclear magnetic resonance (NMR), mass spectrometry, ¹³C NMR calculation in combination with DP4+ and ECD calculations. The antitumor, antibacterial and antifungal activities of the compounds 1-9 were evaluated in vitro. Compound 1 showed antibacterial activity against Acinetobacter baumannii with MIC 42.5 μg/mL. Compounds 1 and 8 exhibited antifungal activity against Candida albicans with MICs 21.5 μg/mL and 17.5 μg/mL, respectively.

A comprehensive benchmark investigation of quantum chemical methods for carbocations

The application of various density functional approximations (DFAs) and an emphasis on popular methods without any consensus have prevailed in computational studies dedicated to carbocations. More importantly, an extensive and rigorous benchmark investigation on density functionals for the class is still lacking. To close this gap, we present a comprehensive benchmark study of quantum chemical methods on a series of classical and nonclassical carbocations, the CARBO33 dataset. We evaluate a total of 107 DFT methods from all rungs giving particular attention to double hybrid density functionals as the potential of the class has been largely undermined in the context of carbocations. To support our findings, DLPNO-CCSD(T) at the complete basis set (CBS) limit and W1-F12 are used as reference methods. Our results indicate that the composite CBS-QB3 method performs poorly and should not be adopted for target energies. Oftentimes, the tested DFAs of a lower rung perform better than several DFAs in a higher rung of Perdew's "Jacob's ladder". Nonetheless, double hybrids DSD-PBEP86-NL and ωB97X-2-D3(BJ) stand out by showing the overall best performance. Among the hybrids evaluated, about half of them show mean absolute deviation (MAD) below 1.1 kcal mol^-1, including the popular hybrids M06-2X and mPW1PW91. In this family, MN15-D3(BJ) performs particularly well (MAD = 0.77 kcal mol^-1) displaying reliable results across various tests. Highly popular B3LYP exhibited one of the worst performances (MAD = 4.74 kcal mol^-1), and we do not recommend its application to carbocations. We also assess the 24 general-purpose basis sets of single- up to quadruple-ζ quality. The best compromise between accuracy and computational cost is achieved with cc-pVTZ followed by def2-TZVP. Computations on larger structures of general interest, including terpene carbocations, are also presented for selected DFT methods confirming general trends in the results.

Efficient Calculation of NMR Shielding Constants Using Composite Method Approximations and Locally Dense Basis Sets

This paper presents a systematic study of applying composite method approximations with locally dense basis sets (LDBS) to efficiently calculate NMR shielding constants in small and medium-sized molecules. The pcSseg-n series of basis sets are shown to have similar accuracy to the pcS-n series when n ≥ 1 and can slightly reduce computational costs. We identify two different LDBS partition schemes that perform very effectively for density functional calculations. We select a large subset of the recent NS372 database containing 290 H, C, N, and O shielding values evaluated by reference methods on 106 molecules to carefully assess methods of the high, medium, and low computational costs to make practical recommendations. Our assessment covers conventional electronic structure methods (density functional theory and wave function) with global basis calculations, as well as their use in one of the satisfactory LDBS approaches, and a range of composite approaches, also with and without LDBS. Altogether 99 methods are evaluated. On this basis, we recommend different methods to reach three different levels of accuracy and time requirements across the four nuclei considered.

Improving IDP theoretical chemical shift accuracy and efficiency through a combined MD/ADMA/DFT and machine learning approach

This work extends the multi-scale computational scheme for the quantum mechanics (QM) calculations of Nuclear Magnetic Resonance (NMR) chemical shifts (CSs) in proteins that lack a well-defined 3D structure. The scheme couples the sampling of an intrinsically disordered protein (IDP) by classical molecular dynamics (MD) with protein fragmentation using the adjustable density matrix assembler (ADMA) and density functional theory (DFT) calculations. In contrast to our early investigation on IDPs (Pavlíková Přecechtělová et al., J. Chem. Theory Comput., 2019, 15, 5642-5658) and the state-of-the art NMR calculations for structured proteins, a partial re-optimization was implemented on the raw MD geometries in vibrational normal mode coordinates to enhance the accuracy of the MD/ADMA/DFT computational scheme. In addition, machine-learning based cluster analysis was performed on the scheme to explore its potential in producing protein structure ensembles (CLUSTER ensembles) that yield accurate CSs at a reduced computational cost. The performance of the cluster-based calculations is validated against results obtained with conventional structural ensembles consisting of MD snapshots extracted from the MD trajectory at regular time intervals (REGULAR ensembles). CS calculations performed with the refined MD/ADMA/DFT framework employed the 6-311++G(d,p) basis set that outperformed IGLO-III calculations with the same density functional approximation (B3LYP) and both explicit and implicit solvation. The partial geometry optimization did not universally improve the agreement of computed CSs with the experiment but substantially decreased errors associated with the ensemble averaging. A CLUSTER ensemble with 50 structures yielded ensemble averages close to those obtained with a REGULAR ensemble consisting of 500 MD frames. The cluster based calculations thus required only a fraction of the computational time.

May the Force (Field) Be with You: On the Importance of Conformational Searches in the Prediction of NMR Chemical Shifts

NMR data prediction is increasingly important in structure elucidation. The impact of force field selection was assessed, along with geometry and energy cutoffs. Based on the conclusions, we propose a new approach named mix-J-DP4, which provides a remarkable increase in the confidence level of complex stereochemical assignments-100% in our molecular test set-with a very modest increment in computational cost.

Citrinin Monomer, Trimer, and Tetracyclic Alkaloid Derivatives from the Hydrothermal Vent-Associated Fungus Penicillium citrinum TW132-59

Five new unusual citrinin-derived alkaloids with a tetracyclic core, citrinidines A-E (1-5), two new amide alkaloids, methyl (2S,8E)-1'-(2-methyl-3-oxodec-8-enamido) butanoate (6) and (2S,8E)-2-methyl-3-oxodec-8-enamide (7), a new unusual citrinin trimer, tricitrinol C (8), a new citrinin acetal-ketal derivative, citrininol (9), together with four known citrinin monomers (10-13), and three known citrinin dimers (14-16), were isolated from the fermentation of hydrothermal vent-associated fungus Penicillium citrinum TW132-59. Their structures were unambiguously determined by nuclear magnetic resonance (NMR), mass spectrometry, Mosher's method, ¹³C NMR calculation in combination with DP4+, and ECD calculations. A plausible biosynthetic pathway of all new compounds (1-9) was proposed. Citrinin trimer (8) exhibited potent cytotoxicity activity with an IC₅₀ value of 1.34 ± 0.11 μM, and compounds 1 and 15 showed moderate cytotoxicity with IC₅₀ values of 17.50 ± 1.43 and 9.45 ± 0.55 μM, respectively, against A549 cell line.

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.

¹H and ¹³C chemical shifts of 35 small, rigid molecules were measured under standardized conditions in CDCl₃ and in CCl₄. Specific solvent interactions lead to chemical shift differences that cannot be reproduced by DFT in implicit solvent.

Exploring gabosine and chlorogentisyl alcohol derivatives from a marine-derived fungus as EcGUS inhibitors with informatic assisted approaches

β-Glucuronidase catalyzes the cleavage of glucuronosyl-O-bonds, whose inhibitors reduce the level of toxic substances present in the intestine caused by anti-cancer and anti-inflammatory therapies. Herein, we presented a new tool, Bioactive Fractions Filtering Platform (BFFP), which is able to reliably discern active candidate node from crude extracts. The source code for the BFFP is available on GitHub (https://github.com/BioGavin/msbff). With the assistant of BFFP, 25 gabosine and chlorogentisyl alcohol derivatives including 19 new compounds were isolated from a marine-derived fungus Epicoccum sp. GST-5. Compounds 7, 9-15 possessed an unusual hybrid skeleton of gabosine and chlorogentisyl alcohol units. Compounds 9-12, 16 and 17 possessed a novel three-membered spiral ring skeleton with one/two gabosine and one/two chlorogentisyl alcohol units. Compound 25 represented new gabosine-derived skeleton possessing an unusual 6/6/6/5/6 condensed ring system. All isolates were evaluated for in vitro E. coli β-glucuronidase (EcGUS) inhibitory activity. 14 Compounds demonstrated superior inhibitory activity (IC₅₀ = 0.24-4.61 μM) to that of standard d-saccharic acid 1,4-lactone (DSL, IC₅₀ = 56.74 ± 4.01 μM). Compounds with chlorogentisyl alcohol moiety, such as 17 (IC₅₀ = 0.24 ± 0.02 μM) and 1 (IC₅₀ = 0.74 ± 0.03 μM), exhibited the most potent inhibitory activity. Furthermore, literature based QSAR profiling by applying PCA and OPLS analysis was carried out to analyze the features of compounds against EcGUS, revealing that the introduction of substituents able to form polar interactions with binding sites of receptor would lead to more active structures.

Substitution Effects on the Reactivity and Thermostability of Five-Membered Ring Fluorides

Recently, five-membered ring fluorides (c-C5Fs) have been significantly desirable in green chlorofluorocarbon substitutes due to their practically flexible application in various fields and environmental friendliness. Detailed knowledge regarding different substitution effects on their environmental properties and thermal stability is very limited due to their high-cost experiments. Here, comprehensive density functional theory and ab initio molecular dynamics calculations were performed to explore the relative electrophilic and nucleophilic reactivity and thermostability of c-C5F chemicals. The electronic properties induced by substitution effects of c-C5Fs were first explored. The environmental friendliness of c-C5Fs including 1,1,2,2,3,3-hexafluorocyclopentane (F6A), 1,1,2,2,3,3,4-heptafluorocyclopentane (F7A), cis-1,1,2,2,3,3,4,5-octafluorocyclopentane (F8A), 3,3,4,4,5,5-hexafluorocyclopentene (F6E), 1,3,3,4,4,5,5-heptafluorocyclopentene (F7E), octafluorocyclopentene (F8E), 1-chloro-3,3,4,4,5,5-hexafluorocyclopent-1-ene (F6-1), and 1-chloro-2,3,3,4,4,5,5-heptafluorocyclopent-1-ene (F7-1) was validly confirmed. Besides, their thermal stabilities at 600 K temperature were concluded due to their flexible carbon skeletons, where both in-plane stability and slight aromaticity of F6E were in peculiar found to contribute substantially. We also would like to stress the future application of F6-1 due to its significant out-plane stability. This study may pave the way for the development of chlorofluorocarbon substitutes.

Calculating bond dissociation energies of X-H (X=C, N, O, S) bonds of aromatic systems via density functional theory: a detailed comparison of methods

In this study, the performance of 17 different density functional theory functionals was compared for the calculation of the bond dissociation energy (BDE) values of X-H (X=C, N, O, S) bonds of aromatic compounds. The effect of the size of the basis set (expansions of 6-31(G)) was also assessed for the initial geometry and zero-point energy calculations, followed by the single-point BDE calculations with different model chemistries with the 6-311 + (3df,2p) basis set. It was found that the size of the basis set for geometry optimization has a much smaller effect on the accuracy of BDE than the choice of functional for the following single-point calculations. The M06-2X, M05-2X and M08-HX functionals yielded highly accurate BDE values compared to experimental data (with the average mean unsigned error MUE = 1.2-1.5 kcal mol^-1), performing better than any of the other functionals. The results suggest that geometry optimization may be performed with B3LYP functional and a small basis set, whereas the M06-2X, M05-2X and M08-HX density functionals with a suitably large basis set offer the best method for calculating BDEs of ArX-H (X=C, N, O, S) bonds.

Accurate Prediction of Nuclear Magnetic Resonance Parameters via the XYG3 Type of Doubly Hybrid Density Functionals

Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful and versatile tools in elucidating molecular structures. To eliminate ambiguities of experimental assignments, accurate calculations of NMR spectra are of great importance. Here, a method for theoretical evaluation of the NMR shielding constants by analytic derivatives using gauge including atomic orbitals (GIAO) has been implemented for the XYG3 type of doubly hybrid density functionals (xDH), namely, the GIAO-xDH method. Benchmark calculations on shielding constants and chemical shifts demonstrate the remarkable accuracy of the GIAO-xDH method, compared to the accurate CCSD(T) references. It is shown here that the XYGJ-OS functional is able to give a mean absolute deviation (MAD) of ∼3.0 ppm in the calculated shielding constants for ¹³C, ¹⁵N, ¹⁷O, ¹⁹F, while both XYGJ-OS and xDH-PBE0 functionals are able to provide a satisfactory estimation of chemical shifts with MADs of ∼0.03 and 1.0 ppm for ¹H and ¹³C, respectively. The basis set influence upon the method has been examined and a computational scheme considering both accuracy and efficiency has been proposed and tested to predict the experimental ¹³C chemical shifts of five medium-sized natural product molecules, yielding a MAD of ∼1.0 ppm, which demonstrates the practical feasibility of the GIAO-xDH method.

New Cytotoxic Secondary Metabolites from Two Deep-Sea-Derived Fungi and the Co-Culture Impact on the Secondary Metabolic Patterns

In this study, chemical profiles for two co-existing deep-sea-derived Penicillium fungal strains were thoroughly investigated. Two new compounds and 11 known compounds were identified from Penicillium sp. LXY140-R, while one new compound and 12 known compounds were isolated from Penicillium sp. LXY140-3. Their structures were elucidated by extensive 1D and 2D NMR experiments, which were supported by HR-ESI-MS data. The antiproliferative activities of all isolates against HCT-116, A549 and Bel-7402 cell lines were also evaluated. Compounds 2, 5, 6, 10 and 13 showed potent antiproliferative activity. To reveal the metabolic relationship of the two strains, we conducted co-culture experiments to discover cross-talk molecules by a device that allows only small molecule to communicate. Extensive HPLC/MS² experiments were applied to identify the disturbance of the chemical profiles within the synthetic Penicillium-Penicillium community. The fungal strain LXY140-R was found to accumulate mono or multiple-acetylation derivatives of deoxynivalenol (DON) sesquiterpenes as responsible molecules by the disturbance of the metabolites produced by the LXY140-3 strain.

High Level Electronic Structure Calculation of Molecular Solid-State NMR Shielding Constants

In this work, we present a quantum mechanics/molecular mechanics (QM/MM) approach for the computation of solid-state nuclear magnetic resonance (SS-NMR) shielding constants (SCs) for molecular crystals. Besides applying standard-DFT functionals like GGAs (PBE), meta-GGAs (TPSS), and hybrids (B3LYP), we apply a double-hybrid (DSD-PBEP86) functional as well as MP2, using the domain-based local pair natural orbital (DLPNO) formalism, to calculate the NMR SCs of six amino acid crystals. All the electronic structure methods used exhibit good correlation of the NMR shieldings with respect to experimental chemical shifts for both ¹H and ¹³C. We also find that local electronic structure is much more important than the long-range electrostatic effects for these systems, implying that cluster approaches using all-electron/Gaussian basis set methods might offer great potential for predictive computations of solid-state NMR parameters for organic solids.

Unprecedented diterpenoid dimers with soluble epoxide hydrolase inhibitory effect from Euphorbia fischeriana

Biseuphoids A (1) and B (2), two unprecedented ent-abietane-type diterpenoid dimers linked by monomeric blocks through C-17-C-12' and C-17-C-11', respectively, were isolated from Euphorbia fischeriana, along with their biogenesis related diterpenoid monomers, 17-hydroxyjolkinolide B (3), caudicifolin (4), and fischeriabietane C (5). Their structures were elucidated by extensive spectroscopy assisted by quantum chemical NMR and ECD calculations. The unusual dimeric skeletons are possibly derived from the adduct of diterpenoid monomers through Michael-like reactions. The novel dimers 1 and 2 exhibited inhibitory activities on soluble epoxide hydrolase (sEH) with IC₅₀ values of 8.17 and 5.61 μM, respectively. Molecular dynamics studies illustrated that both 1 and 2 can occupy the catalytic pocket of sEH by forming stable hydrogen bonds with the key amino acid residues including Gln384, Asn378, Pro361, Ala365, Asn366, and Asn472.

Benchmark Study on the Calculation of 119Sn NMR Chemical Shifts

A new benchmark set termed SnS51 for assessing quantum chemical methods for the computation of ¹¹⁹Sn NMR chemical shifts is presented. It covers 51 unique ¹¹⁹Sn NMR chemical shifts for a selection of 50 tin compounds with diverse bonding motifs and ligands. The experimental reference data are in the spectral range of ±2500 ppm measured in seven different solvents. Fifteen common density functional approximations, two scalar- and one spin-orbit relativistic approach are assessed based on conformer ensembles generated using the CREST/CENSO scheme and state-of-the-art semiempirical (GFN2-xTB), force field (GFN-FF), and composite DFT methods (r²SCAN-3c). Based on the results of this study, the spin-orbit relativistic method combinations of SO-ZORA with PBE0 or revPBE functionals are generally recommended. Both yield mean absolute deviations from experimental data below 100 ppm and excellent linear regression determination coefficients of ≤0.99. If spin-orbit calculations are not affordable, the use of SR-ZORA with B3LYP or X2C with ωB97X or M06 may be considered to obtain qualitative predictions if no severe spin-orbit effects, for example, due to heavy nuclei containing ligands, are expected. An empirical linear scaling correction is demonstrated to be applicable for further improvement, and respective empirical parameters are given. Conformational effects on chemical shifts are studied in detail but are mostly found to be small. However, in specific cases when the ligand sphere differs substantially between conformers, chemical shifts can change by up to several hundred ppm.

Extended Benchmark Set of Main-Group Nuclear Shielding Constants and NMR Chemical Shifts and Its Use to Evaluate Modern DFT Methods

An extended theoretical benchmark set, NS372, for light main-group nuclear shieldings and NMR shifts has been constructed based on high-level GIAO-CCSD(T)/pcSseg-3//CCSD(T)/cc-pVQZ reference data. After removal of the large static-correlation cases O₃, F₃^-, and BH from the statistical evaluations for the ¹⁷O, ¹⁹F, and ¹¹B subsets, the benchmark comprises overall 372 shielding values in 117 molecules with a wide range of electronic-structure situations, containing 124 ¹H, 14 ¹¹B, 93 ¹³C, 43 ¹⁵N, 31 ¹⁷O, 47 ¹⁹F, 14 ³¹P, and 6 ³³S shielding constants. The CCSD(T)/pcSseg-3 data are shown to be close to the basis-set and method limit and thus provide an excellent benchmark to evaluate more approximate methods, such as density functional approaches. This dataset has been used to evaluate Hartree-Fock (HF) and MP2, and a wide range of exchange-correlation functionals from local density approximation (LDA) to generalized gradient approximations (GGAs) and meta-GGAs (focusing on their current-density functional implementations), as well as global hybrid, range-separated hybrid, local hybrid, and double-hybrid functionals. Starting with absolute shielding constants, the DSD-PBEP86 double hybrid is confirmed to provide the highest accuracy, with an aggregate relative mean absolute error (rel. MAE) of only 0.9%, followed by MP2 (1.1%). MP2 and double hybrids only show larger errors for a few systems with the largest static-correlation effects. The double-hybrid B2GP-PLYP, the two local hybrids cLH12ct-SsirPW92 and cLH12ct-SsifPW92, and the current-density functional meta-GGA cB97M-V follow closely behind (all 1.5%), as do some further functionals, cLH20t and cMN15-L (both 1.6%), as well as B2PLYP and KT3 (both 2.0%). Functionals on the lower rungs of the usual ladder offer the advantage of lower computational cost and access to larger molecules. Closer examination also reveals the best-performing methods for individual nuclei in the test set. Different ways of treating τ-dependent functionals are evaluated. When moving from absolute shielding constants to chemical shifts, some of the methods can benefit from systematic error compensation, and the overall error range somewhat narrows. Further methods now achieve the 2% threshold of relative MAEs, including functionals based on TPSS (TPSSh, cmPSTS).