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The landscapes of observed and predicted three-dimensional crystal packing arrangements of small-molecule drug candidates can be complex. The possible appearance of a more thermodynamically stable solid form during drug development has led to the digital workflow of informatics-based risk assessments, named a Solid Form Health Check. Herein, we describe the use of a combined approach consisting of experiments, informatics together with energetic calculations in analysis of four competing polymorphs of PF-06282999, a myeloperoxidase (MPO) inhibitor with conformational flexibility and multiple plausible hydrogen bond networks. This combined approach offered a comprehensive understanding of the solid form structure, properties, and performance, ensuring robust solid form derisking and selection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol -1 at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases., (open access.)

A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures., (open access.)

Fingerprint detection is still the primary investigative technique for deciphering criminal inquiries and identifying individuals. The main forensic fingerprinting reagents (FFRs) currently in use can require multiple treatment steps to produce fingerprints of sufficient quality. Therefore, the development of new, more effective FFRs that require minimal chemical treatment is of great interest in forensic chemistry. In this work, prudently crafted density functional theory and time-dependent density functional theory calculations are utilized to derive mechanistic insight into the optical activity of the non-fluorescent product of ninhydrin, diketohydrindylidenediketohydrindamine (DYDA), and fluorescent product of DFO (1,8-diazafluoren-9-one). We investigate various protonation sites to gain an understanding of isomeric preference in the solid-state material. A relaxed scan of a single torsion angle rotation in the S 1 minimized geometry of the O-protonated DYDA isomer suggests a conical intersection upon ∼10° rotation. We show that the absence of a rigid hydrogen-bonded network in the crystal structure of DYDA supports the hypothesis of torsion rotation, which leads de-excitation to occur readily. Conversely, for the fluorescent DFO product, our calculations support an avoided crossing suggestive of a non-radiative mechanism when the torsion angle is rotated by about ∼100°. This mechanistic insight concurs with experimental observations of fluorescence activity in DFO and may aid the photophysical understanding of poorly visualized fingerprints due to weak fluorescence. We show that identifying suggestive avoided crossings via the method described here can be used to initialize thoughts toward the computational design of FFRs.