Ab initiocalculations of NMR chemical shifts

Analytical Second-Order Properties for the Random Phase Approximation: Nuclear Magnetic Resonance Shieldings

A method for the analytical computation of nuclear magnetic resonance (NMR) shieldings within the direct random phase approximation (RPA) is presented. As a starting point, we use the RPA ground-state energy expression within the resolution-of-the-identity approximation in the atomic-orbital formalism. As has been shown in a recent benchmark study using numerical second derivatives [Glasbrenner, M. J. Chem. Theory Comput. 2022, 18, 192], RPA based on a Hartree-Fock reference shows accuracies comparable to coupled cluster singles and doubles (CCSD) for NMR chemical shieldings. Together with the much lower computational cost of RPA, it has emerged as an accurate method for the computation of NMR shieldings. Therefore, we aim to extend the applicability of RPA NMR to larger systems by introducing analytical second-order derivatives, making it a viable method for the accurate and efficient computation of NMR chemical shieldings.

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.

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.

Effects of the Hubbard potential on the NMR shielding and optoelectronic properties of BiMnVO5 compound

This study explores the nuclear magnetic shielding, chemical shifts, and the optoelectronic properties of the BiMnVO₅ compound using the full-potential linearized augmented plane wave method within the generalized gradient approximation by employing the Hubbard model (GGA + U). The ²⁰⁹Bi and ⁵¹V chemical shifts and bandgap values of the BiMnVO₅ compound in a triclinic crystal structure are found to be directly related to Hubbard potential. The relationship between the isotropic nuclear magnetic shielding σ_iso and chemical shift δ_iso is obtained with a slope of 1.0231 and - 0.00188 for ²⁰⁹Bi and ⁵¹V atoms, respectively. It is also observed that the bandgap, isotropic nuclear magnetic shielding, and chemical shifts increase with the change in Hubbard potentials (U) of 3, 4, 5, 6, and 7.

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%.

An automated framework for high-throughput predictions of NMR chemical shifts within liquid solutions

Identifying stable speciation in multi-component liquid solutions is fundamentally important to areas from electrochemistry to organic chemistry and biomolecular systems. Here we introduce a fully automated, high-throughput computational framework for the accurate prediction of stable species in liquid solutions by computing the nuclear magnetic resonance (NMR) chemical shifts. The framework automatically extracts and categorizes hundreds of thousands of atomic clusters from classical molecular dynamics simulations, identifies the most stable species in solution and calculates their NMR chemical shifts via density functional theory calculations. Additionally, the framework creates a database of computed chemical shifts for liquid solutions across a wide chemical and parameter space. We compare our computational results to experimental measurements for magnesium bis(trifluoromethanesulfonyl)imide Mg(TFSI)2 salt in dimethoxyethane solvent. Our analysis of the Mg2+ solvation structural evolutions reveals key factors that influence the accuracy of NMR chemical shift predictions in liquid solutions. Furthermore, we show how the framework reduces the performance of over 300 13C and 600 1H density functional theory chemical shift predictions to a single submission procedure.

Imaging active site chemistry and protonation states: NMR crystallography of the tryptophan synthase α-aminoacrylate intermediate

NMR-assisted crystallography-the integrated application of solid-state NMR, X-ray crystallography, and first-principles computational chemistry-holds significant promise for mechanistic enzymology: by providing atomic-resolution characterization of stable intermediates in enzyme active sites, including hydrogen atom locations and tautomeric equilibria, NMR crystallography offers insight into both structure and chemical dynamics. Here, this integrated approach is used to characterize the tryptophan synthase α-aminoacrylate intermediate, a defining species for pyridoxal-5'-phosphate-dependent enzymes that catalyze β-elimination and replacement reactions. For this intermediate, NMR-assisted crystallography is able to identify the protonation states of the ionizable sites on the cofactor, substrate, and catalytic side chains as well as the location and orientation of crystallographic waters within the active site. Most notable is the water molecule immediately adjacent to the substrate β-carbon, which serves as a hydrogen bond donor to the ε-amino group of the acid-base catalytic residue βLys87. From this analysis, a detailed three-dimensional picture of structure and reactivity emerges, highlighting the fate of the L-serine hydroxyl leaving group and the reaction pathway back to the preceding transition state. Reaction of the α-aminoacrylate intermediate with benzimidazole, an isostere of the natural substrate indole, shows benzimidazole bound in the active site and poised for, but unable to initiate, the subsequent bond formation step. When modeled into the benzimidazole position, indole is positioned with C3 in contact with the α-aminoacrylate Cβ and aligned for nucleophilic attack. Here, the chemically detailed, three-dimensional structure from NMR-assisted crystallography is key to understanding why benzimidazole does not react, while indole does.

Efficient low-scaling computation of NMR shieldings at the second-order Møller-Plesset perturbation theory level with Cholesky-decomposed densities and an attenuated Coulomb metric

A method for the computation of nuclear magnetic resonance (NMR) shieldings with second-order Møller-Plesset perturbation theory (MP2) is presented which allows to efficiently compute the entire set of shieldings for a given molecular structure. The equations are derived using Laplace-transformed atomic orbital second-order Møller-Plesset perturbation theory as a starting point. The Z-vector approach is employed for minimizing the number of coupled-perturbed self-consistent-field equations that need to be solved. In addition, the method uses the resolution-of-the-identity approximation with an attenuated Coulomb metric and Cholesky decomposition of pseudo-density matrices. The sparsity in the three-center integrals is exploited with sparse linear algebra approaches, leading to reduced computational cost and memory demands. Test calculations show that the deviations from NMR shifts obtained with canonical MP2 are small if appropriate thresholds are used. The performance of the method is illustrated in calculations on DNA strands and on glycine chains with up to 283 atoms and 2864 basis functions.

A framework for automated structure elucidation from routine NMR spectra

Methods to automate structure elucidation that can be applied broadly across chemical structure space have the potential to greatly accelerate chemical discovery. NMR spectroscopy is the most widely used and arguably the most powerful method for elucidating structures of organic molecules. Here we introduce a machine learning (ML) framework that provides a quantitative probabilistic ranking of the most likely structural connectivity of an unknown compound when given routine, experimental one dimensional ¹H and/or ¹³C NMR spectra. In particular, our ML-based algorithm takes input NMR spectra and (i) predicts the presence of specific substructures out of hundreds of substructures it has learned to identify; (ii) annotates the spectrum to label peaks with predicted substructures; and (iii) uses the substructures to construct candidate constitutional isomers and assign to them a probabilistic ranking. Using experimental spectra and molecular formulae for molecules containing up to 10 non-hydrogen atoms, the correct constitutional isomer was the highest-ranking prediction made by our model in 67.4% of the cases and one of the top-ten predictions in 95.8% of the cases. This advance will aid in solving the structure of unknown compounds, and thus further the development of automated structure elucidation tools that could enable the creation of fully autonomous reaction discovery platforms.

A machine learning model and graph generator were able to accurately predict for the presence of nearly 1000 substructures and the connectivity of small organic molecules from experimental 1D NMR data.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Accurate and cost-effective NMR chemical shift predictions for proteins using a molecules-in-molecules fragmentation-based method

We have developed an efficient protocol using our two-layer Molecules-in-Molecules (MIM2) fragmentation-based quantum chemical method for the prediction of NMR chemical shifts of large biomolecules. To investigate the performance of our fragmentation approach and demonstrate its applicability, MIM-NMR calculations are first calibrated on a test set of six proteins. The MIM2-NMR method yields a mean absolute deviation (MAD) from unfragmented full molecule calculations of 0.01 ppm for 1H and 0.06 ppm for 13C chemical shifts. Thus, the errors from fragmentation are only about 3% of our target accuracy of ∼0.3 ppm for 1H and 2-3 ppm for 13C chemical shifts. To compare with experimental chemical shifts, a standard protocol is first derived using two smaller proteins 2LHY (176 atoms) and 2LI1 (146 atoms) for obtaining an appropriate protein structure for NMR chemical shift calculations. The effect of the solvent environment on the calculated NMR chemical shifts is incorporated through implicit, explicit, or explicit-implicit solvation models. The expensive first solvation shell calculations are replaced by a micro-solvation model in which only the immediate interaction between the protein and the explicit solvation environment is considered. A single explicit water molecule for each amine and amide proton is found to be sufficient to yield accurate results for 1H chemical shifts. The 1H and 13C NMR chemical shifts calculated using our protocol give excellent agreement with experiments for two larger proteins, 2MC5 (the helical part with 265 atoms) and 3UMK (33 residue slice with 547 atoms). Overall, our target accuracy of ∼0.3 ppm for 1H and ∼2-3 ppm for 13C has been achieved for the larger proteins. The proposed MIM-NMR method is accurate and computationally cost-effective and should be applicable to study a wide range of large proteins.

Efficient affinity ranking of fluorinated ligands by 19F NMR: CSAR and FastCSAR

Fluorine NMR has recently gained high popularity in drug discovery as it allows efficient and sensitive screening of large numbers of ligands. However, the positive hits found in screening must subsequently be ranked according to their affinity in order to prioritize them for follow-up chemistry. Unfortunately, the primary read-out from the screening experiments, namely the increased relaxation rate upon binding, is not proportional to the affinity of the ligand, as it is polluted by effects such as exchange broadening. Here we present the method CSAR (Chemical Shift-anisotropy-based Affinity Ranking) for reliable ranking of fluorinated ligands by NMR, without the need of isotope labeled protein, titrations or setting up a reporter format. Our strategy is to produce relaxation data that is directly proportional to the binding affinity. This is achieved by removing all other contributions to relaxation as follows: (i) exchange effects are efficiently suppressed by using high power spin lock pulses, (ii) dipolar relaxation effects are approximately subtracted by measuring at two different magnetic fields and (iii) differences in chemical shift anisotropy are normalized using calculated values. A similar ranking can be obtained with the simplified approach FastCSAR that relies on a measurement of a single relaxation experiment at high field (preferably > 600 MHz). An affinity ranking obtained in this simple way will enable prioritizing ligands and thus improve the efficiency of fragment-based drug design.

Oxygen Reduction Assisted by the Concert of Redox Activity and Proton Relay in a Cu(II) Complex

A copper complex, [Cu(dpaq)](ClO₄) (1), of a monoanionic pentadentate amidate ligand (dpaq) has been isolated and characterized to study its efficacy toward electrocatalytic reduction of oxygen in neutral aqueous medium. The Cu(II) mononuclear complex, poised in a distorted trigonal bipyramidal structure, reduces oxygen at an onset potential of 0.50 V vs RHE. Kinetics study by hydrodynamic voltammetry and chronoamperometry suggests a stepwise mechanism for sequential reduction of O₂ to H₂O₂ to H₂O at a single-site Cu-catalyst. The foot-of-the-wave analysis records a turnover frequency of 5.65 × 10² s^-1. At pH 7.0, complex 1 undergoes a quasi-reversible mixed metal-ligand-based reduction and triggers the reduction of dioxygen to water. Electrochemical studies in tandem with quantum chemical investigation, conducted at different redox states, portray the active participation of ligand in completing the process of proton-coupled electron transfer internally. The protonated carboxamido moiety acts as a proton relay, while the quinoline-based orbital supplies the necessary redox equivalent for the conversion of complex 1 to Cu(II)-hydroperoxo species. Thus, a suitable combination of redox non-innocence and proton shuttling functionality in the ligand makes it an effective electron-proton-transfer mediator and subsequently assists the process of oxygen reduction.

A KNIME Workflow for Automated Structure Verification

Adequate characterization of chemical entities made for biological screening in the drug discovery context is critical. Incorrectly characterized structures lead to mistakes in the interpretation of structure-activity relationships and confuse an already multidimensional optimization problem. Mistakes in the later use of these compounds waste money and valuable resources in a discovery process already under cost pressure. Left unidentified, these errors lead to problems in project data packages during quality review. At worst, they put intellectual property and patent integrity at risk. We describe a KNIME workflow for the early and automated identification of these errors during registration of a new chemical entity into the corporate screening catalog. This Automated Structure Verification workflow provides early identification (within 24 hours) of missing or inconsistent analytical data and therefore reduces any mistakes that inevitably get made. Automated identification removes the burden of work from the chemist submitting the compound into the registration system. No additional work is required unless a problem is identified and the submitter alerted. Before implementation, 14% of samples within the existing sample catalog were missing data on initial pass. A year after implementation, only 0.2% were missing data.

Bonding between electron-deficient atoms: strong Lewis-acid character preserved in X–Y–X (X = B, Al; Y = Be, Mg) bridges

Beryllium bis(diazaborolyl) derivatives and their Mg and Al-containing analogues are stable compounds stabilized through covalent bonds between electron-deficient atoms, and behave as good Lewis acids.

Unlocking the potential of late-stage functionalisation: an accurate and fully automated method for the rapid characterisation of multiple regioisomeric products

An automated pipeline for structure determination is outlined that will help unlock the potential of late-stage functionalisation (LSF).

Exploiting in-situ solid-state NMR spectroscopy to probe the early stages of hydration of calcium aluminate cement

We report a high-field in-situ solid-state NMR study of the hydration of CaAl₂O₄ (the most important hydraulic phase in calcium aluminate cement), based on time-resolved measurements of solid-state ²⁷Al NMR spectra during the early stages of the reaction. A variant of the CLASSIC NMR methodology, involving alternate recording of direct-excitation and MQMAS ²⁷Al NMR spectra, was used to monitor the ²⁷Al species present in both the solid and liquid phases as a function of time. Our results provide quantitative information on the changes in the relative amounts of ²⁷Al sites with tetrahedral coordination (the anhydrous reactant phase) and octahedral coordination (the hydrated product phases) as a function of time, and reveal significantly different kinetic and mechanistic behaviour of the hydration reaction at the different temperatures (20 °C and 60 °C) studied.

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.

Exploring Molecular Speciation and Crystallization Mechanism of Amorphous 2-Phenylamino Nicotinic Acid

PURPOSE

Molecular understanding of phase stability and transition of the amorphous state helps in formulation and manufacturing of poorly-soluble drugs. Crystallization of a model compound, 2-phenylamino nicotinic acid (2PNA), from the amorphous state was studied using solid-state analytical methods. Our previous report suggests that 2PNA molecules mainly develop intermolecular -COOH∙∙∙pyridine N (acid-pyridine) interactions in the amorphous state. In the current study, the molecular speciation is explored with regard to the phase transition from the amorphous to the crystalline state.

METHODS

Using spectroscopic techniques, the molecular interactions and structural evolvement during the recrystallization from the glassy state were investigated.

RESULTS

The results unveiled that the structurally heterogeneous amorphous state contains acid-pyridine aggregates - either as hydrogen-bonded neutral molecules or as zwitterions - as well as a population of carboxylic acid dimers. Phase transition from the amorphous state results in crystal structures composed of carboxylic acid dimer (acid-acid) synthon or acid-pyridine chains depending on the crystallization conditions employed.

CONCLUSIONS

The study underlines the structural evolvement, as well as its impact on the metastability, of amorphous samples from local, supramolecular assemblies to long-range intermolecular ordering through crystallization.

Crystal packing and crystallization tendency from the melt of 2-((2-ethylphenyl)amino)nicotinic acid

2-((2-ethylphenyl)amino)nicotinic acid (2EPNA) was synthesized and its crystal structure was determined. It was observed that alkylation of the phenyl ring with ethyl group disrupts the planar conformation of the molecule by steric repulsion, resulting in formation of an acid-pyridine heterosynthon (instead of acid-acid homosynthon) in the crystal. Crystallization tendency from the melt state of the polymorph was studied by differential scanning calorimetry (DSC). It was revealed that this compound could form a very stable amorphous phase on melt quenching and not crystallize even on re-heating. The formation of acid-pyridine hydrogen bonding in the amorphous state is believed to be responsible for its good glass forming ability.

Toward Closing the Gap: Quantum Mechanical Calculations and Experimentally Measured Chemical Shifts of a Microcrystalline Lectin

NMR chemical shifts are exquisitely sensitive probes for conformation and dynamics in molecules and supramolecular assemblies. Although isotropic chemical shifts are easily measured with high accuracy and precision in conventional NMR experiments, they remain challenging to calculate quantum mechanically, particularly in inherently dynamic biological systems. Using a model benchmark protein, the 133-residue agglutinin from Oscillatoria agardhii (OAA), which has been extensively characterized by us previously, we have explored the integration of X-ray crystallography, solution NMR, MAS NMR, and quantum mechanics/molecular mechanics (QM/MM) calculations for analysis of 13Cα and 15NH isotropic chemical shifts. The influence of local interactions, quaternary contacts, and dynamics on the accuracy of calculated chemical shifts is analyzed. Our approach is broadly applicable and expected to be beneficial in chemical shift analysis and chemical-shift-based structure refinement for proteins and protein assemblies.

Investigation of two- and three-bond carbon-hydrogen coupling constants in cinnamic acid based compounds

Two- and three-bond coupling constants (² J_HC and ³ J_HC ) were determined for a series of 12 substituted cinnamic acids using a selective 2D inphase/antiphase (IPAP)-single quantum multiple bond correlation (HSQMBC) and 1D proton coupled ¹³ C NMR experiments. The coupling constants from two methods were compared and found to give very similar values. The results showed coupling constant values ranging from 1.7 to 9.7 Hz and 1.0 to 9.6 Hz for the IPAP-HSQMBC and the direct ¹³ C NMR experiments, respectively. The experimental values of the coupling constants were compared with discrete density functional theory (DFT) calculated values and were found to be in good agreement for the ³ J_HC . However, the DFT method under estimated the ² J_HC coupling constants. Knowing the limitations of the measurement and calculation of these multibond coupling constants will add confidence to the assignment of conformation or stereochemical aspects of complex molecules like natural products. Copyright © 2016 John Wiley & Sons, Ltd.

(1)H NMR spectra of alcohols in hydrogen bonding solvents: DFT/GIAO calculations of chemical shifts

Proton nuclear magnetic resonance (NMR) shifts of aliphatic alcohols in hydrogen bonding solvents have been computed on the basis of density functional theory by applying the gauge-including atomic orbital method to geometry-optimized alcohol/solvent complexes. The OH proton shifts and hydrogen bond distances for methanol or ethanol complexed with pyridine depend very much on the functional employed and very little on the basis set, provided it is sufficiently large to give the correct quasi-linear hydrogen bond geometry. The CH proton shifts are insensitive to both the functional and the basis set. NMR shifts for all protons in several alcohol/pyridine complexes are calculated at the Perdew, Burke and Ernzerhof PBE0/cc-pVTZ//PBE0/6-311 + G(d,p) level in the gas phase. The results correlate with the shifts for the pyridine-complexed alcohols, determined by analysing data from the NMR titration of alcohols against pyridine. More pragmatically, computed shifts for a wider range of alcohols correlate with experimental shifts in neat pyridine. Shifts for alcohols in dimethylsulfoxide, based on the corresponding complexes in the gas phase, correlate well with the experimental values, but the overall root mean square difference is high (0.23 ppm), shifts for the OH, CHOH and other CH protons being systematically overestimated, by averages of 0.42, 0.21 and 0.06 ppm, respectively. If the computed shifts are corrected accordingly, a very good correlation is obtained with a gradient of 1.00 ± 0.01, an intercept of 0.00 ± 0.02 ppm and a root mean square difference of 0.09 ppm. This is a modest improvement on the result of applying the CHARGE programme to a slightly different set of alcohols. Some alcohol complexes with acetone and acetonitrile were investigated both in the gas phase and in a continuum of the relevant solvent.

Effect of Co-Ordination Chemistry and Oxidation State on the (207)Pb Magnetic-Shielding Tensor: A DFT/ZORA Investigation

The magnetic shielding tensor of (207)Pb is calculated for various solids exhibiting (1) a holodirected lead(II) center containing a stereochemically inactive lone pair, (2) a hemidirected lead(II) center with a stereochemically active lone-pair, or (3) a lead(IV) center. Tensors investigated at the scalar relativistic level are compared with those calculated with the full ZORA/spin-orbit Hamiltonian. The effect of using GGA density functionals is compared to the use of hybrid density functionals.

(77)Se chemical shift tensor of L-selenocystine: experimental NMR measurements and quantum chemical investigations of structural effects

The genetically encoded amino acid selenocysteine and its dimeric form, selenocystine, are both utilized by nature. They are found in active sites of selenoproteins, enzymes that facilitate a diverse range of reactions, including the detoxification of reactive oxygen species and regulation of redox pathways. Due to selenocysteine and selenocystine's specialized biological roles, it is of interest to examine their (77)Se NMR properties and how those can in turn be employed to study biological systems. We report the solid-state (77)Se NMR measurements of the L-selenocystine chemical shift tensor, which provides the first experimental chemical shift tensor information on selenocysteine-containing systems. Quantum chemical calculations of L-selenocystine models were performed to help understand various structural effects on (77)Se L-selenocystine's chemical shift tensor. The effects of protonation state, protein environment, and substituent of selenium-bonded carbon on the isotropic chemical shift were found to be in a range of ca. 10-20 ppm. However, the conformational effect was found to be much larger, spanning ca. 600 ppm for the C-Se-Se-C dihedral angle range of -180° to +180°. Our calculations show that around the minimum energy structure with a C-Se-Se-C dihedral angle of ca. -90°, the energy costs to alter the dihedral angle in the range from -120° to -60° are within only 2.5 kcal/mol. This makes it possible to realize these conformations in a protein or crystal environment. (77)Se NMR was found to be a sensitive probe to such changes and has an isotropic chemical shift range of 272 ± 30 ppm for this energetically favorable conformation range. The energy-minimized structures exhibited calculated isotropic shifts that lay within 3-9% of those reported in previous solution NMR studies. The experimental solid-state NMR isotropic chemical shift is near the lower bound of this calculated range for these readily accessible conformations. These results suggest that the dihedral information may be deduced for a protein with appropriate structural models. These first-time experimental and theoretical results will facilitate future NMR studies of selenium-containing compounds and proteins.

Accurate ab initio prediction of NMR chemical shifts of nucleic acids and nucleic acids/protein complexes

NMR chemical shift predictions based on empirical methods are nowadays indispensable tools during resonance assignment and 3D structure calculation of proteins. However, owing to the very limited statistical data basis, such methods are still in their infancy in the field of nucleic acids, especially when non-canonical structures and nucleic acid complexes are considered. Here, we present an ab initio approach for predicting proton chemical shifts of arbitrary nucleic acid structures based on state-of-the-art fragment-based quantum chemical calculations. We tested our prediction method on a diverse set of nucleic acid structures including double-stranded DNA, hairpins, DNA/protein complexes and chemically-modified DNA. Overall, our quantum chemical calculations yield highly/very accurate predictions with mean absolute deviations of 0.3–0.6 ppm and correlation coefficients (r²) usually above 0.9. This will allow for identifying misassignments and validating 3D structures. Furthermore, our calculations reveal that chemical shifts of protons involved in hydrogen bonding are predicted significantly less accurately. This is in part caused by insufficient inclusion of solvation effects. However, it also points toward shortcomings of current force fields used for structure determination of nucleic acids. Our quantum chemical calculations could therefore provide input for force field optimization.

1H and 13C NMR scaling factors for the calculation of chemical shifts in commonly used solvents using density functional theory

Calculation of NMR chemical shifts and coupling constants using quantum mechanical calculations [density functional theory (DFT)], has become a very popular tool for the determination of conformation and the assignment of stereochemistry within a molecule. We present the scaling factors (linear regression parameters) from 10 DFT methods for 10 commonly used NMR solvents using the same set of reference compounds. The results were compared with the corresponding gas-phase calculations to assess the inclusion of the polarizable continuum model for solvent effects.

A guide to small-molecule structure assignment through computation of (¹H and ¹³C) NMR chemical shifts

This protocol is intended to provide chemists who discover or make new organic compounds with a valuable tool for validating the structural assignments of those new chemical entities. Experimental ¹H and/or ¹³C NMR spectral data and its proper interpretation for the compound of interest is required as a starting point. The approach involves the following steps: (i) using molecular mechanics calculations (with, e.g., MacroModel) to generate a library of conformers; (ii) using density functional theory (DFT) calculations (with, e.g., Gaussian 09) to determine optimal geometry, free energies and chemical shifts for each conformer; (iii) determining Boltzmann-weighted proton and carbon chemical shifts; and (iv) comparing the computed chemical shifts for two or more candidate structures with experimental data to determine the best fit. For a typical structure assignment of a small organic molecule (e.g., fewer than ∼10 non-H atoms or up to ∼180 a.m.u. and ∼20 conformers), this protocol can be completed in ∼2 h of active effort over a 2-d period; for more complex molecules (e.g., fewer than ∼30 non-H atoms or up to ∼500 a.m.u. and ∼50 conformers), the protocol requires ∼3-6 h of active effort over a 2-week period. To demonstrate the method, we have chosen the analysis of the cis- versus the trans-diastereoisomers of 3-methylcyclohexanol (1-cis versus 1-trans). The protocol is written in a manner that makes the computation of chemical shifts tractable for chemists who may otherwise have only rudimentary computational experience.

Analysis of seven-membered lactones by computational NMR methods: proton NMR chemical shift data are more discriminating than carbon

We report an NMR chemical shift study of conformationally challenging seven-membered lactones (1-11); computed and experimental data sets are compared. The computations involved full conformational analysis of each lactone, Boltzmann-weighted averaging of the chemical shifts across all conformers, and linear correction of the computed chemical shifts. DFT geometry optimizations [M06-2X/6-31+G(d,p)] and GIAO NMR chemical shift calculations [B3LYP/6-311+G(2d,p)] provided the computed chemical shifts. The corrected mean absolute error (CMAE), the average of the differences between the computed and experimental chemical shifts for each of the 11 lactones, is encouragingly small (0.02-0.08 ppm for (1)H or 0.8-2.2 ppm for (13)C). Three pairs of cis versus trans diastereomeric lactones were used to assess the ability of the method to distinguish between stereoisomers. The experimental shifts were compared with the computed shifts for each of the two possible isomers. We introduce the use of a "match ratio"--the ratio of the larger CMAE (worse fit) to the smaller CMAE (better fit). A greater match ratio value indicates better distinguishing ability. The match ratios are larger for proton data [2.4-4.0 (av = 3.2)] than for carbon [1.1-2.3 (av = 1.6)], indicating that the former provide a better basis for discriminating these diastereomers.

Conformational and NMR study of some furan derivatives by DFT methods

4'-substituted neutral/protonated furfurylidenanilines and trans-styrylfurans are able to exist in two different conformations related to the rotation around the furan ring-bridge double bond. In this work, the equilibrium geometry and the corresponding rotational barrier of the benzene ring for each furan derivative conformation were calculated by DFT methods. The trend and shape of the rotational barrier are rationalized within natural bond orbitals as well as atoms-in-molecules approach. For the corresponding equilibrium geometries, (1)H and (13)C substituent induced shifts (SIS) were calculated and compared with experimental values. Calculated shielding constants are shown to be sensitive to the substituent effect through a linear fit with substituent's Hammett constants. An alternative approach was followed for assessing the effect of substituents over SIS through comparing the differences in isotropic shielding constants with NBO charges as well as with (1)H and (13)C experimental chemical shifts.

Conformational Sampling by Ab Initio Molecular Dynamics Simulations Improves NMR Chemical Shift Predictions

Car-Parrinello molecular dynamics simulations were performed for N-methyl acetamide as a small test system for amide groups in protein backbones, and NMR chemical shifts were calculated based on the generated ensemble. If conformational sampling and explicit solvent molecules are taken into account, excellent agreement between the calculated and experimental chemical shifts is obtained. These results represent a landmark improvement over calculations based on classical molecular dynamics (MD) simulations especially for amide protons, which are predicted too high-field shifted based on the latter ensembles. We were able to show that the better results are caused by the solute-solvents interactions forming shorter hydrogen bonds as well as by the internal degrees of freedom of the solute. Inspired by these results, we propose our approach as a new tool for the validation of force fields due to its power of identifying the structural reasons for discrepancies between the experimental and calculated data.

Anti-inflammatory and antinociceptive activity of epiisopiloturine, an imidazole alkaloid isolated from Pilocarpus microphyllus

The aim of this study was to investigate the antinociceptive and anti-inflammatory activities of epiisopiloturine (1), an imidazole alkaloid found in the leaves of Pilocarpus microphyllus. The anti-inflammatory activity of 1 was evaluated using several agents that induce paw edema and peritonitis in Swiss mice. Paw tissue and peritoneal fluid samples were obtained to determine myeloperoxidase (MPO) activity or tumor necrosis factor (TNF)-α and interleukin (IL)-1β levels. The antinociceptive activity was evaluated by acetic acid-induced writhing, the hot plate test, and pain induction using formalin. Compared to vehicle treatment, pretreatment with 1 (0.1, 0.3, and 1 mg/kg, ip) of mice significantly reduced carrageenan-induced paw edema (p < 0.05). Furthermore, compound 1 at a dose of 1 mg/kg effectively inhibited edema induced by dextran sulfate, serotonin, and bradykinin, but had no effect on histamine-induced edema. The administration of 1 (1 mg/kg) following carrageenan-induced peritonitis reduced total and differential peritoneal leukocyte counts and also carrageenan-induced paw MPO activity and TNF-α and IL-1β levels in the peritoneal cavity. Pretreatment with 1 also reduced acetic acid-induced writhing and inhibited the first and second phases of the formalin test, but did not alter response latency in the hot plate test. Pretreatment with naloxone reversed the antinociceptive effect of 1.

Industrial Scale Isolation, Structural and Spectroscopic Characterization of Epiisopiloturine from Pilocarpus microphyllus Stapf Leaves: A Promising Alkaloid against Schistosomiasis

This paper presents an industrial scale process for extraction, purification, and isolation of epiisopiloturine (EPI) (2(3H)-Furanone,dihydro-3-(hydroxyphenylmethyl)-4-[(1-methyl-1H-imidazol-4-yl)methyl]-, [3S-[3a(R*),4b]]), which is an alkaloid from jaborandi leaves (Pilocarpus microphyllus Stapf). Additionally for the first time a set of structural and spectroscopic techniques were used to characterize this alkaloid. EPI has shown schistomicidal activity against adults and young forms, as well as the reduction of the egg laying adult worms and low toxicity to mammalian cells (in vitro). At first, the extraction of EPI was done with toluene and methylene chloride to obtain a solution that was alkalinized with ammonium carbonate. The remaining solution was treated in sequence by acidification, filtration and alkalinization. These industrial procedures are necessary in order to remove impurities and subsequent application of the high performance liquid chromatography (HPLC). The HPLC was employed also to remove other alkaloids, to obtain EPI purity higher than 98%. The viability of the method was confirmed through HPLC and electrospray mass spectrometry, that yielded a pseudo molecular ion of m/z equal to 287.1 Da. EPI structure was characterized by single crystal X-ray diffraction (XRD), (1)H and (13)C nuclear magnetic resonance (NMR) in deuterated methanol/chloroform solution, vibrational spectroscopy and mass coupled thermal analyses. EPI molecule presents a parallel alignment of the benzene and the methyl imidazol ring separated by an interplanar spacing of 3.758 Å indicating a π-π bond interaction. The imidazole alkaloid melts at 225°C and decomposes above 230°C under air. EPI structure was used in theoretical Density Functional Theory calculations, considering the single crystal XRD data in order to simulate the NMR, infrared and Raman spectra of the molecule, and performs the signals attribution.

Chemical shifts in biomolecules

NMR chemical shifts are sensitive probes of structure and dynamics in proteins. Empirical models, based on a large database of measured shifts, take an input structure and provide increasingly accurate estimates of the corresponding shifts. Quantum chemical calculations can provide the same information, with greater generality but (currently) with less accuracy. These methods are now providing new ways to approach NMR structure determination, and new insights into the conformational dynamics of proteins.

Quantum chemical calculations of amide-15N chemical shift anisotropy tensors for a membrane-bound cytochrome-b5

There is considerable interest in determining amide-(15)N chemical shift anisotropy (CSA) tensors from biomolecules and understanding their variation for structural and dynamics studies using solution and solid-state NMR spectroscopy and also by quantum chemical calculations. Due to the difficulties associated with the measurement of CSA tensors from membrane proteins, NMR-based structural studies heavily relied on the CSA tensors determined from model systems, typically single crystals of model peptides. In the present study, the principal components of backbone amide-(15)N CSA tensors have been determined using density functional theory for a 16.7 kDa membrane-bound paramagnetic heme containing protein, cytochrome-b(5) (cytb(5)). All the calculations were performed by taking residues within 5 Å distance from the backbone amide-(15)N nucleus of interest. The calculated amide-(15)N CSA spans agree less well with our solution NMR data determined for an effective internuclear distance r(N-H) = 1.023 Å and a constant angle β = 18° that the least shielded component (δ(11)) makes with the N-H bond. The variation of amide-(15)N CSA span obtained using quantum chemical calculations is found to be smaller than that obtained from solution NMR measurements, whereas the trends of the variations are found to be in close agreement. We believe that the results reported in this study will be useful in studying the structure and dynamics of membrane proteins and heme-containing proteins, and also membrane-bound protein-protein complexes such as cytochromes-b5-P450.

SYNTHESIS AND GIAO NMR CALCULATIONS FOR TWO DIASTEREOISOMERS OF 2′-ACETYLOXY-2′-PHENYLSPIRO[INDENO[1,2-b]QUINOXALIN-11,1′-CYCLOPROPANE]

Two diastereoisomers of 2′-acetyloxy-2′-phenylspiro[indeno[1,2-b]quinoxalin-11,1′-cyclopropane] were synthesized and their 1 H NMR spectra were recorded. Their chemical structures were fully optimized at B3LYP/6-311+G(d,p) level of theory using the Gaussian 03W program package. The 1 H NMR chemical shifts were calculated for geometry-optimized structures of the diastereoisomers with the gauge independent atomic orbital (GIAO) and B3LYP method with the 6-311+G(d,p), 6-311++G(d), 6-31++G(d,p) and 6-31+G(d) basis sets. The computational results were then compared with the experimental values and the structures associated with each spectrum were assigned.

Toward the Quantum Chemical Calculation of NMR Chemical Shifts of Proteins. 3. Conformational Sampling and Explicit Solvents Model

Fragment-based quantum chemical calculations are able to accurately calculate NMR chemical shifts even for very large molecules like proteins. But even with systematic optimization of the level of theory and basis sets as well as the use of implicit solvents models, some nuclei like polar protons and nitrogens suffer from poor predictions. Two properties of the real system, strongly influencing the experimental chemical shifts but almost always neglected in the calculations, will be discussed here in great detail: (1) conformational averaging and (2) interactions with first-shell solvent molecules. Classical molecular dynamics simulations in explicit water were carried out for obtaining a representative ensemble including the arrangement of neighboring solvent molecules, which was then subjected to quantum chemical calculations. We could demonstrate with the small test system N-methyl acetamide (NMA) that the calculated chemical shifts show immense variations of up to 6 ppm and 50 ppm for protons and nitrogens, respectively, depending on the snapshot taken from a classical molecular dynamics simulation. Applying the same approach to the HA2 domain of the influenza virus glycoprotein hemagglutinin, a 32-amino-acid-long polypeptide, and comparing averaged values to the experiment, chemical shifts of nonpolar protons and carbon atoms in proteins were calculated with unprecedented accuracy. Additionally, the mean absolute error could be reduced by a factor of 2.43 for polar protons, and reasonable correlations were obtained for nitrogen and carbonyl carbon in contrast to all other studies published so far.