Shift Calculations Research Articles

The interplay of density functional selection and crystal structure for accurate NMR chemical shift predictions.

Ab initio chemical shift prediction plays a central role in nuclear magnetic resonance (NMR) crystallography, and the accuracy with which chemical shifts can be predicted relative to experiment impacts the confidence with which structures can be assigned. For organic crystals, periodic density functional theory calculations with the gauge-including projector augmented wave (GIPAW) approximation and the PBE functional are widely used at present. Many previous studies have examined how using more advanced density functionals can increase the accuracy of predicted chemical shifts relative to experiment, but nearly all of those studies employed crystal structures that were optimized with generalized-gradient approximation (GGA) functionals. Here, we investigate how the accuracy of the predicted chemical shifts in organic crystals is affected by replacing GGA-level PBE-D3(BJ) crystal geometries with more accurate hybrid functional PBE0-D3(BJ) ones. Based on benchmark data sets containing 132 13C and 35 15N chemical shifts, plus case studies on testosterone, acetaminophen, and phenobarbital, we find that switching from GGA-level geometries and chemical shifts to hybrid-functional ones reduces 13C and 15N chemical shift errors by ∼40-60% versus experiment. However, most of the improvement stems from the use of the hybrid functional for the chemical shift calculations, rather than from the refined geometries. In addition, even with the improved geometries, we find that double-hybrid functionals still do not systematically increase chemical shift agreement with experiment beyond what hybrid functionals provide. In the end, these results suggest that the combination of GGA-level crystal structures and hybrid-functional chemical shifts represents a particularly cost-effective combination for NMR crystallography in organic systems.

The accuracy limit of chemical shift predictions for species in aqueous solution.

Interpreting NMR experiments benefits from first-principles predictions of chemical shifts. Reaching the accuracy limit of theory is relevant for unambiguous structural analysis and dissecting theoretical approximations. Since accurate chemical shift measurements are based on using internal reference compounds such as trimethylsilylpropanesulfonate (DSS), a detailed comparison of experimental with theoretical data requires simultaneous consideration of both target and reference species ensembles in the same solvent environment. Here we show that ab initio molecular dynamics simulations to generate liquid-state ensembles of target and reference compounds, including explicitly their short-range solvation environments and combined with quantum-mechanical solvation models, allows for predicting highly accurate 1H (∼0.1-0.5 ppm) and aliphatic 13C (∼1.5 ppm) chemical shifts for aqueous solutions of the model compounds trimethylamine N-oxide (TMAO) and N-methylacetamide (NMA), referenced to DSS without any system-specific adjustments. This encompasses the two peptide bond conformations of NMA identified by NMR. The results are used to derive a general-purpose guideline set for predictive NMR chemical shift calculations of NMA in the liquid state and to identify artifacts of force field models. Accurate predictions are only obtained if a sufficient number of explicit water molecules is included in the quantum-mechanical calculations, disproving a purely electrostatic model of the solvent effect on chemical shifts.

Impacts of basis sets, solvent models, and NMR methods on the accuracy of 1H and 13C chemical shift calculations for biaryls: a DFT study

Introduction: Biaryls are core structures composed of chiral ligands, organocatalysts, biologically active natural products and biopolymer lignins. In this study, the effects of basis sets, solvent models, and NMR methods on the accuracy of 1H/13C NMR chemical shift calculations for biaryl structures were evaluated. Methods: All calculations were performed using Gaussian09. The GIAO NMR results were observed and extracted using GaussView05. To reduce the systematic error of the calculations, linear regression analysis of the calculated chemical shifts versus the experimental shifts was performed. Results: The tested basis sets showed good 1H/13C results, with CMAE values as low as 0.0425 ppm and 1.09 ppm for 1H and 13C, respectively. The use of solvent models significantly increased the accuracy of the 1H chemical shift calculations. The GIAO method produced more accurate results than did the IGAIM and CSGT methods. Conclusion: This study recommends 6-31G(d,p) and DGDZVP basis sets, IEMPCM and CPCM solvent models, and GIAO NMR methods for the accurate prediction of 1H and 13C chemical shifts for biaryls, assisting in their full structural assignments.

Pinuseldarone, a Clerodane-Type Diterpene from Pinus eldarica Needles and Phytochemicals as Novel Agents for Regulating Brown Adipogenesis and Thermogenesis.

Phytochemical investigation of the MeOH extract of Pinus eldarica needles led to the isolation and identification of a new clerodane-type diterpene, pinuseldarone (1), along with a known flavonoid, 5,4'-dihydroxy-3,7,8-trimethoxy-6-C-methylflavone (2), through HPLC purification. The structure of the new compound 1 was elucidated using spectroscopic methods, including 1D and 2D NMR, as well as HRESIMS. Its absolute configuration was established through NOESY analysis and computational methods, including electronic circular dichroism (ECD) calculations and gauge-including atomic orbital NMR chemical shift calculations, followed by DP4+ probability analysis. The metabolic implications of the isolated compounds were assessed using a cultured brown adipocyte model derived from murine brown adipose tissue. It was observed that treatment with dihydroxy-3,7,8-trimethoxy-6-C-methylflavone (2) downregulates the adipogenic marker C/EBPδ and fatty acid transporter CD36, resulting in a significant reduction in lipid accumulation during brown adipocyte differentiation. However, pinuseldarone (1) treatment did not affect brown adipocyte differentiation. Interestingly, pretreatment with pinuseldarone (1) potentiated the pharmacological stimulation of brown adipocytes, seemingly achieved by sensitizing their response to β3-adrenoreceptor signaling. Therefore, our findings indicate that phytochemicals derived from P. eldarica needles could potentially serve as valuable compounds for adjusting the metabolic activity of brown adipose tissue, a vital component in maintaining whole-body metabolic homeostasis.

Linear Extension of Carbaporphyrin Chromophores: Synthesis, Protonation, and Metalation of Anthro[2,3-b]carbaporphyrins: Evidence for 30π-Electron Aromatic Circuits in a Palladium(II) Complex.

Acid-catalyzed condensation of a naphtho[2,3-f]indane dialdehyde with a tripyrrane, followed by an oxidation step, afforded an anthro[2,3-b]-21-carbaporphyrin. The presence of a fused anthracene unit induced minor bathochromic shifts and did not significantly affect the aromatic characteristics of the carbaporphyrin core. Protonation led to the formation of a monocation with similar diatropic properties, but the dication generated in the presence of a large excess of trifluoroacetic acid had a weakened Soret band absorption and a broad absorption at 754 nm. Nucleus-independent chemical shift (NICS) calculations indicate that the dication is only weakly aromatic and possesses a 32-atom 30π electron delocalization pathway. Alkylation with methyl iodide and potassium carbonate gave a 22-methyl derivative that reacted with palladium(II) acetate to afford an aromatic palladium(II) complex. Upon heating, the methyl group migrated from the nitrogen to the internal carbon atom and the resulting complex exhibited diminished aromatic character. A comparison with related carbaporphyrin complexes without ring fusion or with benzo- or naphtho-fused units demonstrated that the diatropic character decreased with increasing conjugation. NICS calculations and anisotropy of induced current density (AICD) plots confirmed this trend and showed that the remaining aromatic properties of the anthrocarbaporphyrin complex were due to a 30π electron circuit that extends around the entire anthracene unit.

Exact two-component theory becoming an efficient tool for NMR shieldings and shifts with spin–orbit coupling

We present a gauge-origin invariant exact two-component (X2C) approach within a modern density functional framework, supporting meta-generalized gradient approximations such as TPSS and range-separated hybrid functionals such as CAM-B3LYP. The complete exchange-correlation kernel is applied, including the direct contribution of the field-dependent basis functions and the reorthonormalization contribution from the perturbed overlap matrix. Additionally, the finite nucleus model is available for the electron-nucleus potential and the vector potential throughout. Efficiency is ensured by the diagonal local approximation to the unitary decoupling transformation in X2C as well as the (multipole-accelerated) resolution of the identity approximation for the Coulomb term (MARI-J, RI-J) and the seminumerical exchange approximation. Errors introduced by these approximations are assessed and found to be clearly negligible. The applicability of our implementation to large-scale calculations is demonstrated for a tin pincer-type system as well as low-valent tin and lead complexes. Here, the calculation of the Sn nuclear magnetic resonance shifts for the pincer-type ligand with about 2400 basis functions requires less than 1 h for hybrid density functionals. Further, the impact of spin–orbit coupling on the nucleus-independent chemical shifts and the corresponding ring currents of all-metal aromatic systems is studied.

An Evaluation of the Signal to Noise Ratio (SNR) of Next Generation Wireless Communication Systems using Large Intelligent Surfaces: Deep Learning Approach

The existing data rate must be greatly increased in order to support the numerous applications of the next generation communication systems. Using Large Intelligent Surfaces (LIS), which are a panel with mounted reflective components, is one way to address this problem. Their primary function is to divert the electromagnetic signal to the intended user. As a result, the received signal's strength and reception quality both improve, improving the Quality of Service (QoS). Machine Learning algorithms have been used to implement LIS in a number of ways, including channel estimation and the calculation of phase shifts (discrete), to mention a few. Here, it is suggested that the Signal to Noise Ratio (SNR) for a LIS-supported communication system be assessed using a Deep Learning (DL) model. On the DL model, the effects of the SGD, Adam RMSProp Adadelta and Adamax optimizers are investigated. The Mean Squared Error (MSE) loss function is taken into account. The Adam optimizer offers the highest level of precision, making it preferable to other optimizers. The SNR for 10 users is measured using the suggested DL model with Adam Optimizer. The outcomes of this work is contrasted with the SNR estimate by an existing technique that calculates SNR based on LIS size and the location of transmitter and receiver with an accuracy of 93.5%. The simulation results indicate that the accuracy is increased to 96% using the suggested DL model which attains an average error of 3.6.

A new steroid with potent antimicrobial activities and two new polyketides from Penicillium variabile EN-394, a fungus obtained from the marine red alga Rhodomela confervoides.

Three new compounds, including one steroid named penivariod A (1) and two polyketides penivarides A and B (2 and 3), as well as six known derivatives (4-9) were isolated from Penicillium variabile EN-394, a fungus afforded from the marine red alga Rhodomela confervoides. Their structures were elucidated by analysis of the HRESIMS, 1D and 2D NMR. The absolute stereochemistry was determined by X-ray crystallographic data, gauge-independent atomic orbital (GIAO) NMR shift calculation followed by DP4+ analysis combined with calculated electronic circular dichroism (ECD). Antimicrobial activities for the new compounds (1-3) were evaluated against human- and aquatic-pathogenic bacteria as well as plant pathogenic fungi. Compound 1 exhibited potent antimicrobial activity against most of the pathogenic strains, especially for Escherichia coli and Pseudomonas aeruginosa, with MIC values of 1.0 and 2.0 μg ml-1, respectively.

Eleuthemarins A and B, two new isocoumarin derivatives from the Arctic fungus Eleutheromyces sp. CPCC 401592.

Two new isocoumarin derivatives, eleuthemarins A (1) and B (2), were isolated from the Arctic fungus Eleutheromyces sp. CPCC 401592. Their structures and absolute configurations were elucidated through spectroscopic methods, quantum chemical calculations of NMR shifts, and calculated electronic circular dichroism. This is the first report for the chemical investigation of the genus Eleutheromyces. Compounds 1 and 2 showed selective cytotoxic activities against H460, A549, and HCT116 cancer cell lines with IC50 values in the range of 24.1-57.3 μM, respectively. Compound 1 displayed weak antibacterial activities.

Uncertainties in the transport properties of helium gas at cryogenic temperatures determined using molecular dynamics simulation

In this study, the transport properties, such as diffusivity, viscosity, and thermal conductivity, of 4He at the gaseous phase are computed for state points in the temperature range of 10 K to 150 K and pressure range of 0.10 MPa (1 atm) to 0.21 MPa using classical and quantum frameworks. Within the classical molecular dynamics simulation (MDS), the Green–Kubo (GK) approach is used. The GK method has an inherent uncertainty associated with it due to the random fluctuations in the flux autocorrelation functions. Moreover, in the temperature range of 10 K to 40 K, the quantum nature of the helium gas particles becomes prominent. The classical MDS performed does not include these effects and hence introduces uncertainties in the calculated results. We discuss efficient ways of time averaging the autocorrelation function to reduce statistical fluctuations and perform the quantum scattering phase shift calculations within the Chapman–Cowling theory to study the quantum effects. Furthermore, this study also provides the transport properties data in the cryogenic temperature limit of 10 K to 150 K, which is scarcely studied in the literature and can be applied in complex systems.

Young Duality for Variational Inequalities and Nonparametric Method of Demand Analysis in Input–Output Models with Inputs Substitution: Application for Kazakhstan Economy

The global macroeconomic shocks of the last decade entail the restructuring of national production networks and induce processes of input substitution. We suggest mathematical tools of Young duality for variational inequalities for studying these processes. Based on the tools we provide, a new mathematical model of a production network with several final consumers is created. The model is formulated as a pair of conjugated problems: a complementarity problem for optimal resource allocation with neoclassical production functions and the Young dual problem for equilibrium price indices on network products. The solution of these problems gives an equilibrium point in the space of network inter-industry flows and price indices on goods. Based on our previous results, we suggest an algorithm for model identification with an official economic statistic in the case of constant elasticity of substitution production functions. We give an explicit solution to the complementarity problems in this case and develop the algorithm of the inter-industry flows scenario projection. Since the algorithm needs the scenario projection of final sales structure as its input, we suggest a modified methodology that allows the calculation of scenario shifts in final consumer spending. To do this, we employ the generalized nonparametric method of demand analysis. As a result, we develop new technology for scenario calculation of a national input–output table, including shifts in final consumer spending. The technology takes into account a substitution of inputs in the network and is based on officially published national statistics data. The application of the methodology to study tax collection scenarios for Kazakhstan’s production network is demonstrated.

Automated Fragmentation Quantum Mechanical Calculation of 15N and 13C Chemical Shifts in a Membrane Protein.

In this work, we developed an accurate and cost-effective automated fragmentation quantum mechanics/molecular mechanics (AF-QM/MM) method to calculate the chemical shifts of 15N and 13C of membrane proteins. The convergence of the AF-QM/MM method was tested using Krokinobacter eikastus rhodopsin 2 as a test case. When the distance threshold of the QM region is equal to or larger than 4.0 Å, the results of the AF-QM/MM calculations are close to convergence. In addition, the effects of selected density functionals, basis sets, and local chemical environment of target atoms on the chemical shift calculations were systematically investigated. Our results demonstrate that the predicted chemical shifts are more accurate when important environmental factors including cross-protomer interactions, lipid molecules, and solvent molecules are taken into consideration, especially for the 15N chemical shift prediction. Furthermore, with the presence of sodium ions in the environment, the chemical shift of residues, retinal, and retinal Schiff base are affected, which is consistent with the results of the solid-state nuclear magnetic resonance (NMR) experiment. Upon comparing the performance of various density functionals (namely, B3LYP, B3PW91, M06-2X, M06-L, mPW1PW91, OB95, and OPBE), the results show that mPW1PW91 is a suitable functional for the 15N and 13C chemical shift prediction of the membrane proteins. Meanwhile, we find that the improved accuracy of the 13Cβ chemical shift calculations can be achieved by the employment of the triple-ζ basis set. However, the employment of the triple-ζ basis set does not improve the accuracy of the 15N and 13Cα chemical shift calculations nor does the addition of a diffuse function improve the overall prediction accuracy of the chemical shifts. Our study also underscores that the AF-QM/MM method has significant advantages in predicting the chemical shifts of key ligands and nonstandard residues in membrane proteins than most widely used empirical models; therefore, it could be an accurate computational tool for chemical shift calculations on various types of biological systems.

Macrosphelides from Antarctic fungus Pseudogymnoascus sp. (strain SF-7351) and their neuroprotective effects on BV2 and HT22 cells

Strategies for reducing inflammation in neurodegenerative diseases have attracted increasing attention. Herein, we discovered and evaluated the neuroprotective potential of fungal metabolites isolated from the Antarctic fungus Pseudogymnoascus sp. (strain SF-7351). The chemical investigation of the EtOAc extract of the fungal strain isolate revealed a novel naturally occurring epi-macrosphelide J (1), a novel secondary metabolite macrosphelide N (2), and three known compounds, namely macrosphelide A (3), macrosphelide B (4), and macrosphelide J (5). Their structures were established unambiguously using spectroscopic methods, such as one-dimensional and two-dimensional nuclear magnetic resonance (1D and 2D-NMR) spectroscopy, high-resolution electrospray ionization mass spectrometry (HR-ESI-MS), and gauge-including atomic orbital (GIAO) NMR chemical shift calculations, with the support of the advanced statistical method DP4+. Among the isolated metabolites, the absolute configuration of epi-macrosphelide J (1) was further confirmed using single-crystal X-ray diffraction analysis. The neuroprotective effects of the isolated metabolites were evaluated in lipopolysaccharide (LPS)-induced BV2 and glutamate-stimulated HT22 cells. Only macrosphelide B (4) displayed substantial protective effects in both BV2 and HT22 cells. Molecular mechanisms underlying this activity were investigated using western blotting and molecular docking studies. Macrosphelide B (4) inhibited the inflammatory response by reducing the nuclear translocation of NF-κB (p65) in LPS-induced BV2 cells and induced the Nrf2/HO-1 signaling pathway in both BV2 and HT22 cells. The neuroprotective effect of macrosphelide B (4) is related to the interaction between Keap1 and p65. These results suggest that macrosphelide B (4), present in the fungus Pseudogymnoascus sp. (strain SF-7351), may serve as a candidate for the treatment of neurodegenerative diseases.

On the Efficiency of the Density Functional Theory (DFT)-Based Computational Protocol for 1H and 13C Nuclear Magnetic Resonance (NMR) Chemical Shifts of Natural Products: Studying the Accuracy of the pecS-n (n = 1, 2) Basis Sets.

The basis set issue has always been one of the most important factors of accuracy in the quantum chemical calculations of NMR chemical shifts. In a previous paper, we developed new pecS-n (n = 1, 2) basis sets purposed for the calculations of the NMR chemical shifts of the nuclei of the most popular NMR-active isotopes of 1-2 row elements and successfully approbated these on the DFT calculations of chemical shifts in a limited series of small molecules. In this paper, we demonstrate the performance of the pecS-n (n = 1, 2) basis sets on the calculations of as much as 713 1H and 767 13C chemical shifts of 23 biologically active natural products with complicated stereochemical structures, carried out using the GIAO-DFT(PBE0) approach. We also proposed new alternative contraction schemes for our basis sets characterized by less contraction depth of the p-shell. New contraction coefficients have been optimized with the property-energy consistent (PEC) method. The accuracies of the pecS-n (n = 1, 2) basis sets of both the original and newly contracted forms were assessed on massive benchmark calculations of proton and carbon chemical shifts of a vast variety of natural products. It was found that less contracted pecS-n (n = 1, 2) basis sets provide no noticeable improvement in accuracy. These calculations represent the most austere test of our basis sets as applied to routine calculations of the NMR chemical shifts of real-life compounds.

Aaptocarbamates A−G, chlorinated terpene carbamates with antiosteoclastogenic activities from the marine sponge Aaptos sp.

Six undescribed chlorinated sesquiterpene carbamates, aaptocarbamates A–F, and a chlorinated tris-norsesquiterpene carbamate, aaptocarbamate G, were isolated from the marine sponge Aaptos sp. collected in Indonesia. Aaptocarbamates D–F and G possess tetrahydrofurans and a tetrahydrofuranone, respectively. The relative configurations of the tetrahydrofuran units were determined by the NOE correlations and DFT-based calculation of the 13C chemical shifts. This is the first time that chlorinated terpene carbamates have been reported from natural sources. Various aaptamine derivatives have been reported from the Aaptos sponges so far, the isolation of chlorinated terpene carbamates is very rare. Aaptocarbamates A, B, and D showed 60% inhibition of the RANKL-induced formation of multinucleated osteoclasts in RAW264 macrophages at 20 μM.

Discovery of pyranonaphthoquinones and an eighteen-membered ring macrolide from the rhizospheric soil-derived fungus Phialocephala sp. YUD18001 by OSMAC strategy

Two new pyranonaphthoquinones, phialoyxinones A (1) and B (2), a new eighteen-membered ring lactone, phialoyxtone (3), and five known pyranonaphthoquinone derivatives were identified from the fungus Phialocephala sp. YUD18001, which was isolated from the rhizospheric soil associated with Gastrodia elata. Their structures were unequivocally established by a comprehensive interpretation of the spectroscopic data, with the stereochemistry for 1–3 was defined by a combination of TDDFT calculations, and the DP4+ probability analysis based on NMR chemical shift calculations. All of the new compounds 1–3 were evaluated for cytotoxicity and acetylcholinesterase inhibitory, compound 2 exhibited in vitro cytotoxic activities against five human cancer cell lines (HL-60, SMMC-7721, A549, MCF-7 and SW480) with IC50 values ranging from 11.80 to 19.32 μM. Compounds 2 and 3 exhibited moderate AChE inhibitory activities. A putative biosynthetic pathway for the pyranonaphthoquinones was proposed.

Stereochemical assignment of clerodane-type diterpenes from the fruits of Casearia grewiifolia and their ability to inhibit PCSK9 expression

More than 20 natural products have been reported to modulate PCSK9-mediated cholesterol regulation, and small-molecule-derived proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors continue to be developed and identified. Here, twelve undescribed clerodane-type diterpenes (1–9 and 12–14) and two known compounds were isolated from the chloroform-soluble extract of the dried fruits of Casearia grewiifolia Vent. using a PCSK9 mRNA expression monitoring assay. Among the undescribed compounds, the stereochemistry of two diastereomeric grewiifolins A and B (1 and 2) were extensively elucidated using 2D Nuclear Overhauser Effect Spectroscopy (NOESY) experiments, excitation-sculptured indirect detection experiments (EXSIDE), interproton distance analyses, and computational calculations that included quantum chemical shift calculations combined with DP4+ analysis. All isolates were assessed for their inhibitory activity against PCSK9 and IDOL mRNA expression. Among the compounds tested, compound 3 inhibited PCSK9 and IDOL mRNA expression.

Interaction of Methylenecycloalkanes with BF3·THF Catalyzed by 2TiCl2

The Cp2TiCl2-catalyzed interaction of methylenecycloalkanes with BF3·THF in tetrahydrofuran was carried out for the first time with the formation of target 1-fluoro-1-boraspirocarbocycles and also isomerization products of a starting monomer (1-methylcycloalk-1-enes). The structure of reaction products was elucidated using one(1H, 13C Dept, 11B, 19F) and two-dimensional (COSY, HSQC, HMBC) NMR spectroscopy, mass spectrometry combined with quantum-chemical calculations of 13C NMR chemical shifts.

Sarcoeleganolides H–K, new anti-thrombotic cembranes from soft coral Sarcophyton elegans

Chemical investigation of soft coral the Sarcophyton elegans collected from the South China Sea led to the identification of four new cembranes, namely sarcoeleganolides H–K (1–4). Their structures and absolute configurations were established by 1D and 2D NMR spectroscopy, quantum chemical calculations of NMR chemical shifts and electronic circular dichroism (ECD) data analysis. Moreover, compound 2 exhibited moderate anti-thrombotic activity in zebrafish.

The π‐Molecular Complex of Biphenylene and Tetracyanoethylene

AbstractThe investigation of the biphenylene (BP)‐tetracyanoethylene (TCNE) π‐molecular complex is reported. The first study on this complex appeared in 1961 and was considered as a charge transfer complex with a symmetric, co‐planar arrangement of the components. Moreover, it was assumed that this arrangement is not only dictated by the formation of a Mulliken‐type donor‐acceptor complex, but also by the electronic stabilization of the ‘cyclobutadieneoid’ central ring of biphenylene through complex formation. Yet, crystal structure and associated computational analysis have not verified these predictions so far. We found that factors other than charge‐transfer interactions are most influential in the crystal formation. The low association constant in solution, and the weak interaction between the components in the 1 : 1 crystal structure point towards the low contribution of charge transfer interactions to their binding. Nevertheless, the presence of these interaction is hinted by the color of its solution and verified by theoretical calculations. Furthermore, Nucleus Independent Chemical Shift (NICS) calculations were carried out to characterize potential changes in the (anti)aromatic character of BP upon complex formation. The NICS(0) values of the rings of BP exhibit tiny changes both in the BP‐TCNE dimer and in the crystal, which also suggests weak electronic interactions between them.