Publications by authors named "L M Hunnisett"

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.

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Article Synopsis
  • Participants from 22 research groups utilized various methods, including periodic DFT-D methods, machine learning models, and empirical force fields to assess crystal structures generated from standardized sets.
  • The findings indicate that DFT-D methods generally aligned well with experimental results, while one machine learning approach showed significant promise; however, the need for more efficient research methods was emphasized due to resource consumption.
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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.

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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.

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