NMR Crystallography Structure Determinations with ¹H Chemical Shifts. GIPAW DFT Calculation Quality Can Be...

Nuclear magnetic resonance (NMR) crystallography may be used in various solid-state structural characterization tasks. For organic compounds in this context, proton isotropic chemical shifts [δ_iso(¹H)] are routinely used. It is typical to pair experimentally measured proton δ_iso values with δ_iso values that were computationally generated from crystal structure models. This can yield a δ_iso(¹H) root-mean-squared deviation (RMSD) value for each crystal structure model. In this study, we monitor the way in which gauge including projector augmented wave (GIPAW) density functional theory (DFT) computations of ¹H δ_iso values can be influenced by the quality of the computational input parameters. We consider 126 computationally generated (using crystal structure prediction, CSP) crystal structures for three molecules: cocaine (30 structures), flutamide (21 structures), and ampicillin (75 structures). The quality parameters selected are the plane wave energy cutoff (E_cut), and the k-point grid used to sample reciprocal (i.e., momentum) space. We also probe the utility of performing one-parameter and two-parameter linear mappings for transforming computed hydrogen isotropic magnetic shielding values (σ_iso) into computed δ_iso(¹H) values. We find that both E_cut and the k-point grid can be degraded substantially (e.g., E_cut ∼ 25 Ry) and yet still produce very similar computed δ_iso(¹H) values. We consider the mechanisms under GIPAW DFT that contribute to computed hydrogen σ_iso values to help understand this robustness: many contributions are zero or cancel out when converting σ_iso values to δ_iso(¹H) values via the linear mapping. The robust nature of computed δ_iso(¹H) values leads to consistent estimates of δ_iso(¹H) RMSD values. It is then demonstrated using cocaine and flutamide that when δ_iso(¹H) RMSD values are used in NMR crystallography tasks such as structure selection/determination, the quality of the GIPAW DFT computation can be severely degraded and still produce identical outcomes to those that used a more computationally intensive protocol. Ampicillin is selected as a practical example to probe how our findings might reasonably be applied in the structure determination of a complex organic molecule. We propose that relatively modest quality GIPAW DFT computations (i.e., E_cut = 35 Ry and a 1 × 1 × 1 k-point grid) may be used to first filter out obviously poor structure candidates. Subsequently, slightly higher quality GIPAW DFT computations can be used for structure selection/determination. Our findings indicate that it should be possible to, on average, reduce the computational resources required in such NMR crystallography tasks by approximately a factor of 3-4 in terms of CPU time.