An inexpensive density functional theory-based protocol to predict accurate 19 F-NMR chemical shifts

Exploring Geometrical, Electronic and Spectroscopic Properties of 2-Nitroimidazole-Based Radiopharmaceuticals via Computational Chemistry Methods

Tumor hypoxia plays an important role in the clinical management and treatment planning of various cancers. The use of 2-nitroimidazole-based radiopharmaceuticals has been the most successful for positron emission tomography (PET) and single photon emission computed tomography (SPECT) imaging probes, offering noninvasive means to assess tumor hypoxia. In this study we performed detailed computational investigations of the most used compounds for PET imaging, focusing on those derived from 2-nitroimidazole: fluoromisonidazole (FMISO), fluoroazomycin arabinoside (FAZA), fluoroetanidazole (FETA), fluoroerythronitroimidazole (FETNIM) and 2-(2-nitroimidazol-1-yl)-N-(2,2,3,3,3-pentafluoropropyl)acetamide (EF5). Conformational analysis, structural parameters, vibrational IR and Raman properties (within both harmonic and anharmonic approximations), as well as the NMR shielding tensors and spin-spin coupling constants were obtained by density functional theory (DFT) calculations and then correlated with experimental findings, where available. Furthermore, time-dependent DFT computations reveal insight into the excited states of the compounds. Our results predict a significant change in the conformational landscape of most of the investigated compounds when transitioning from the gas phase to aqueous solution. According to computational data, the 2-nitroimidazole moiety determines to a large extent the spectroscopic properties of its derivatives. Due to the limited structural information available in the current literature for the investigated compounds, the findings presented herein deepen the current understanding of the electronic structures of these five radiopharmaceuticals.

Prediction of 19F NMR chemical shifts for organic compounds with ORCA

Accurate assignment of 19F NMR has long been a challenge, and quantum chemical methods are possible solutions. Herein we reported a scaling method for the prediction of 19F NMR chemical shift with freely available ORCA program package. Performance of 31 DFT functionals coupled with 11 basis sets were evaluated and influence of geometry optimization was also studied with five functionals coupled with three basis sets. The significance of geometry was further examined through the execution of relaxed surface scans of seven flexible compounds, and averaged shieldings of obtained conformers yielded notable improvement of the correlation between calculated isotropic shielidings and experimental chemical shifts. Utilization of the best scaling factor obtained successfully assigned of fluorine atoms in multifluorinated molecules with different conformations. The method reported here was computationally inexpensive, easily available with acceptable accuracy.

Simple, accurate, adjustable-parameter-free prediction of NMR shifts for molecules in solution

Accurate prediction of NMR shifts is invaluable for interpreting and assigning NMR spectra, especially for complex applications such as determining the identity of unknown substances or resolving stereochemical assignments. Statistical linear regression models have proven effective for accurately correlating density functional theory predictions of chemical shieldings with experimentally-measured shifts, but lack transferability - they must be reparameterised using a reasonably extensive training set at each level of theory and for each choice of NMR solvent. We have previously introduced a novel two-point "shift-and-scale" correction procedure for gas phase shieldings that overcomes these limitations without significant loss of accuracy. In this work, we demonstrate that this approach is equally applicable for predicting solution-phase shifts from computed gas phase shieldings, using acetaldehyde as an experimentally and computationally convenient reference system. We also present all of the required experimental reference data to enable this approach to be used for any target analyte in a range of commonly used NMR solvents (chloroform, dichloromethane, acetonitrile, methanol, acetone, DMSO, D2O, benzene, pyridine).

Stereochemical dependence of substituent γ-effects in the 19 F NMR shielding constants

The substituent α-, β-, and γ-effects of the elements of the second and third periods on ¹⁹ F NMR chemical shifts are evaluated including the establishment of stereochemical dependence of γ-effect, the latter particularly important in stereochemical studies of fluorine-containing compounds. Benchmark calculations performed for a series of 32 simple inorganic fluorine-containing molecules demonstrated a markedly good correlation between calculated and experimental fluorine chemical shifts characterized by a mean absolute error of 22.5 ppm in the range of about 900 ppm, which corresponds to a 2.5% error in the percentage terms.

A computational tool to accurately and quickly predict 19F NMR chemical shifts of molecules with fluorine-carbon and fluorine-boron bonds

We report the evaluation of density-functional-theory (DFT) based procedures for predicting ¹⁹F NMR chemical shifts at modest computational cost for a range of molecules with fluorine bonds, to be used as a tool for assisting the characterisation of reaction intermediates and products and as an aid to identifying mechanistic pathways. The results for a balanced learning set of molecules were then checked using two further testing sets, resulting in the recommendation of the ωB97XD/aug-cc-pvdz DFT method and basis set as having the best combination of accuracy and computational time, with a RMS error of 3.57 ppm. Cationic molecules calculated without counter-anion showed normal errors, whilst anionic molecules showed somewhat larger errors. The method was applied to the prediction of the conformationally averaged ¹⁹F chemical shifts of 2,2,3,3,4,4,5,5-octafluoropentan-1-ol, in which gauche stereoelectronic effects involving fluorine dominate and to determining the position of coordination equilibria of fluorinated boranes as an aid to verifying the relative energies of intermediate species involved in catalytic amidation reactions involving boron catalysts.

Efficient Screening of Target-Specific Selected Compounds in Mixtures by 19F NMR Binding Assay with Predicted 19F NMR Chemical Shifts

Ligand-based 19 F NMR screening is a highly effective and well-established hit-finding approach. The high sensitivity to protein binding makes it particularly suitable for fragment screening. Different criteria can be considered for generating fluorinated fragment libraries. One common strategy is to assemble a large, diverse, well-designed and characterized fragment library which is screened in mixtures, generated based on experimental 19 F NMR chemical shifts. Here, we introduce a complementary knowledge-based 19 F NMR screening approach, named 19 Focused screening, enabling the efficient screening of putative active molecules selected by computational hit finding methodologies, in mixtures assembled and on-the-fly deconvoluted based on predicted 19 F NMR chemical shifts. In this study, we developed a novel approach, named LEFshift , for 19 F NMR chemical shift prediction using rooted topological fluorine torsion fingerprints in combination with a random forest machine learning method. A demonstration of this approach to a real test case is reported.