Solid‐State NMR‐Driven Crystal Structure Prediction of Molecular Crystals: The Case of Mebendazole

Abstract

Among all possible NMR crystallography approaches for crystal-structure determination, crystal structure prediction -NMR crystallography (CSP-NMRX) has recently turned out to be a powerful method. In the latter, the original procedure exploited solid-state NMR (SSNMR) information during the final steps of the prediction. In particular, it used the comparison of computed and experimental chemical shifts for the selection of the correct crystal packing. Still, the prediction procedure, generally carried out with DFT methods, may require important computational resources and be quite time-consuming, especially if there are no available constraints to use at the initial stage. Herein, the successful application of this combined prediction method, which exploits NMR information also in the input step to reduce the search space of the predictive algorithm, is presented. Herein, this method was applied on mebendazole, which is characterized by desmotropism. The use of SSNMR data as constraints for the selection of the right tautomer and the determination of the number of independent molecules in the unit cell led to a considerably faster process, reducing the number of calculations to be performed. In this way, the crystal packing was successfully predicted for the three known phases of mebendazole. To evaluate the quality of the predicted structures, these were compared to the experimental ones. The crystal structure of phase B of mebendazole, in particular, was determined de novo by powder diffraction and is presented for the first time in this paper.

Along the road to crystal structure prediction (CSP) of pharmaceutical-like molecules

“…, in order to help solve the crystal structure of microcrystalline, powdered samples. 7,17,31,32 A typical CSP protocol follows a multi-step CSP workflow displayed in Fig. 2.…”

Ambiguous structure determination from powder data: four different structural models of 4,11-difluoroquinacridone with similar X-ray powder patterns, fit to the PDF, SSNMR and DFT-D

“…The usefulness and efficacy of this approach has been demonstrated in many fields of science including, for example, pharmaceuticals (Smith et al, 2001;Tatton et al, 2018;Rahal et al, 2021), biology (Reddy et al, 2015;Hughes et al, 2017) and pigments (Tapmeyer et al, 2020). In particular, SSNMR, while also useful for improving the quality of structures solved by single-crystal X-ray diffraction (Rossi et al, 2018;Bernasconi et al, 2020), is able to provide the structure solution, even if SSNMR is combined only with DFT or crystal structure prediction calculations (Elena & Emsley, 2005;Salager et al, 2010;Thureau et al, 2019;Bravetti et al, 2022). Instead of DFT-D, statistical potentials can be used (Hofmann, 1998;Hofmann & Apostolakis, 2003;Hofmann et al, 2004).…”

Advanced Solid-State NMR Analysis of Two Crystal Forms of Ranitidine Hydrochloride: Detection of ¹H–¹⁴N Intra-/Intermolecular Correlations

“…However, preparing suitable single crystals for X-ray crystallography is challenging. Recently, the measurement of molecular correlations using SSNMR has been reported as straightforward method not requiring the preparation of a single crystal, 7,8) but few cases have been reported and it is not yet commonly used for measuring APIs.…”