Improved Quantum Chemical NMR Chemical Shift Prediction of Metabolites in Aqueous Solution toward the Validation of Unknowns.

Abstract

A quantum-chemistry based protocol, termed MOSS-DFT, is presented for the prediction of 13C and 1H NMR chemical shifts of a wide range of organic molecules in aqueous solution, including metabolites. Molecular motif-specific linear scaling parameters are reported for five different density functional theory (DFT) methods (B97-2/pcS-1, B97-2/pcS-2, B97-2/pcS-3, B3LYP/pcS-2, and BLYP/pcS-2), which were applied to a large set of 176 metabolite molecules. The chemical shift root-mean-square deviations (RMSD) for the best method, B97-2/pcS-3, are 1.93 and 0.154 ppm for 13C and 1H chemical shifts, respectively. Excellent results have been obtained for chemical shifts of methyl and aromatic 13C and 1H that are not directly bonded to a heteroatom (O, N, S, or P) with RMSD values of 1.15/0.079 and 1.31/0.118 ppm, respectively. This study not only demonstrates how NMR chemical shift in aqueous environment can be improved over the commonly used global linear scaling approach, but also allows for motif-specific error estimates, which are useful for an improved chemical shift-based verification of metabolite candidates of metabolomics samples containing unknown components.