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The seventh blind test of crystal structure prediction: structure generation methods

Abstract:
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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1107/s2052520624007492

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Role:
Author
ORCID:
0000-0003-0936-2342
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Role:
Author
ORCID:
0000-0002-4707-909X
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Role:
Author
ORCID:
0000-0002-4573-7722


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Funder identifier:
https://ror.org/003x0zc53


Publisher:
International Union of Crystallography
Journal:
Acta Crystallographica Section B, Structural Science, Crystal Engineering, and Materials More from this journal
Volume:
80
Issue:
6
Pages:
517-547
Place of publication:
England
Publication date:
2024-12-01
Acceptance date:
2024-07-30
DOI:
EISSN:
2052-5206
ISSN:
2052-5192
Pmid:
39405196


Language:
English
Keywords:
Pubs id:
2039176
Local pid:
pubs:2039176
Deposit date:
2024-10-28
ARK identifier:

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