Evaluating the accuracy of density functional theory for calculating 1H and 13C NMR chemical shifts in drug molecules

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%.

Conformational Analysis of 5,4'-Dihydroxy-7,5',3'-trimethoxyisoflavone in Solution Using 1H NMR: A Density Functional Theory Approach

Among 20 compounds isolated from the extracts of Ouratea ferruginea the 5,4'-dihydroxy-7,5',3'-trimethoxyisoflavone (9) showed the best inhibitory effect on glutathione S-transferase (GST) and so deserves our attention. In this work we investigated the preferred molecular structure of 9 in chloroform solution using the density functional theory (DFT) and molecular dynamics simulation. Comparison between experimental ¹H NMR data in CDCl₃ solution and calculated chemical shifts enabled us to precisely determine the conformation adopted by 9 in solution, which can be used in further theoretical studies involving interaction with biological targets. Moreover, the experimental NMR data were used as reference to assess the ability of DFT based methods to predict ¹H NMR spectrum in solution for organic compounds. Among various DFT functionals the hybrid B3LYP was the most adequate for the calculation of chemical shifts in what CH_n protons are concerned. Regarding the OH hydrogen, inclusion of explicit CHCl₃ solvent molecules adequately placed around the solute led to good agreement with the experimental chemical shifts (in CDCl₃). It is a well-known fact that theoretical prediction of chemical shifts for OH hydrogens poses as a challenge and also revealed that the way the solvent effects are included in the DFT calculations is crucial for the right prediction of the whole ¹H NMR spectrum. It was found in this work that a supermolecule solute-solvent calculation with a minimum of four CHCl₃ molecules is enough to correctly reproduce the ¹H NMR experimental profile observed in solution, revealing that the calculated solvated structure used to reproduce the NMR chemical shifts is not unique.

New porphyrins: synthesis, characterization, and computational studies

New trans-A₂B₂-porphyrins substituted at phenyl positions were synthesized from 4-methylphthalic acid as a starting material through sequential multistep reactions. These macrocycles were characterized by ¹H NMR, ¹³C NMR, ¹⁹F NMR, ¹H-¹H COSY NMR, and MALDI-TOF mass spectrometry. Computational studies were performed on the porphyrins to investigate various factors such as structural features, electronic energy, energy gaps, and aromaticity. Energy band gap values of these compounds especially N-hydroxyphthalimide-functionalized porphyrins were small that makes them as good candidates for solar cell systems and photocatalysis. Relationships between electronic energies and aromaticity of the compounds were then investigated. The data indicated that the aromaticity features at the center of two series of these compounds (fluorinated and non-fluorinated porphyrins) were in the opposite manner.

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

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

Method Calibration or Data Fitting?

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

Intramolecular hydrogen bonding in conformationally semi-rigid α-acylmethane derivatives: a theoretical NMR study

Conformational mobility is a core property of organic compounds, and conformational analysis has become a pervasive tool for synthetic design. In this work, we present experimental and computational (employing Density Functional Theory) evidence for unusual intramolecular hydrogen bonding interactions in a series of α-acylmethane derivatives, as well as a discussion of the consequences thereof for their NMR spectroscopic properties.

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.

Positional Variance in NMR Crystallography

We propose a method to quantify positional uncertainties in crystal structures determined by chemical-shift-based NMR crystallography. The method combines molecular dynamics simulations and density functional theory calculations with experimental and computational chemical shift uncertainties. In this manner we find the average positional accuracy as well as the isotropic and anisotropic positional accuracy associated with each atom in a crystal structure determined by NMR crystallography. The approach is demonstrated on the crystal structures of cocaine, flutamide, flufenamic acid, the K salt of penicillin G, and form 4 of the drug 4-[4-(2-adamantylcarbamoyl)-5-tert-butylpyrazol-1-yl]benzoic acid (AZD8329). We find that, for the crystal structure of cocaine, the uncertainty corresponds to a positional RMSD of 0.17 Å. This is a factor of 2.5 less than for single-crystal X-ray-diffraction-based structure determination.