NMR Crystallography Structure Determinations with 1H Chemical Shifts. GIPAW DFT Calculation Quality Can Be Substantially Degraded, but Nearly Identical Outputs Relative to Benchmark Computations Are Obtained: Why and So What?

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 [δiso(1H)] are routinely used. It is typical to pair experimentally measured proton δiso values with δiso values that were computationally generated from crystal structure models. This can yield a δiso(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 δiso 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 (Ecut), 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 (σiso) into computed δiso(1H) values. We find that both Ecut and the k-point grid can be degraded substantially (e.g., Ecut ∼ 25 Ry) and yet still produce very similar computed δiso(1H) values. We consider the mechanisms under GIPAW DFT that contribute to computed hydrogen σiso values to help understand this robustness: many contributions are zero or cancel out when converting σiso values to δiso(1H) values via the linear mapping. The robust nature of computed δiso(1H) values leads to consistent estimates of δiso(1H) RMSD values. It is then demonstrated using cocaine and flutamide that when δiso(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., Ecut = 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.