ABSTRACT Chemical shift assignment in solid‐state nuclear magnetic resonance (NMR) is a challenging process that usually relies on a set of 1D and 2D experiments to determine the assignment by establishing connectivities along the covalent backbone. A Bayesian probabilistic assignment method was recently introduced based on a fragment analysis using a database of chemical shifts. Here, we propose a fast 3D structure validation method that utilizes predictions from a crystal structure as a starting point for Bayesian probabilistic chemical shift assignment. We demonstrate the approach with improved confidence in the 1 H and 13 C assignments for the structures of cocaine and Atuliflapon, and finally Lorlatinib which has Z′ = 2.
Rodriguez‐Madrid et al. (Wed,) studied this question.