1H isotropic chemical shift metrics for NMR crystallography of powdered molecular organics

Abstract

Hydrogen magnetic shielding values from gauge including projector augmented wave (GIPAW) density functional theory (DFT) calculations, when combined with experimental solid-state ¹H nuclear magnetic resonance (NMR) chemical shift data collected on powdered microcrystalline organics, have been used to perform various crystal structure characterization tasks (e.g., refinements, verifications, determinations). These tasks fall under the umbrella of ‘NMR crystallography’. In several instances, an isotropic ¹H chemical shift (δ_iso) root-mean-squared deviation (RMSD) metric has been applied during these studies (including the first de novo crystal structure determination: M. Baias, J.-N. Dumez, P. H. Svensson, S. Schantz, G. M. Day and L. Emsley, De Novo Determination of the Crystal Structure of a Large Drug Molecule by Crystal Structure Prediction-Based Powder NMR Crystallography, J. Am. Chem. Soc., 2013, 135, 17501–17507). While it is assumed that the ¹H δ_iso RMSD metrics are converged, our study probes the robustness of these metrics. Specifically, we consider how the structure of the δ_iso(¹H) RMSD metric varies depending on: (i) selected GIPAW DFT input parameters; (ii) the number of fitting parameters used during linear mapping; and (iii) the GIPAW DFT computational software. These δ_iso(¹H) RMSD metrics were produced from a set of 24 benchmark crystal structures (428 crystallographically unique hydrogen atom environments). Interestingly, we find that the δ_iso(¹H) RMSD metric structures are very robust to substantial degradation in the quality of the GIPAW DFT computations, which is unexplored in the NMR crystallography literature as prior studies focus on convergence rather than divergence. We then briefly consider the impact of our findings using the structure determination of thymol as an illustrative example and our results strongly suggest that if δ_iso(¹H) RMSD metrics are being used, then the GIPAW DFT computations can be performed much more efficiently than at present. Overall, this should allow for more efficient NMR crystallography characterization tasks of important materials that contain ¹H nuclei, such as organic pharmaceuticals.