On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorder
Distinguishing disorder into static and dynamic based on multi-temperature X-ray or neutron diffraction experiments is the current state of the art, but is only descriptive, not predictive. Here, several disordered structures are revisited from the Cambridge Crystallographic Data Center `drug subset...
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| Format: | Article |
| Language: | English |
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International Union of Crystallography
2021-03-01
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| Series: | IUCrJ |
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| Online Access: | http://scripts.iucr.org/cgi-bin/paper?S2052252521000531 |
| _version_ | 1798031347434913792 |
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| author | Birger Dittrich |
| author_facet | Birger Dittrich |
| author_sort | Birger Dittrich |
| collection | DOAJ |
| description | Distinguishing disorder into static and dynamic based on multi-temperature X-ray or neutron diffraction experiments is the current state of the art, but is only descriptive, not predictive. Here, several disordered structures are revisited from the Cambridge Crystallographic Data Center `drug subset', the Cambridge Structural Database and own earlier work, where experimental intensities of Bragg diffraction data were available. Using the molecule-in-cluster approach, structures with distinguishable conformations were optimized separately, as extracted from available or generated disorder models of the respective disordered crystal structures. Re-combining these `archetype structures' by restraining positional and constraining displacement parameters for conventional least-squares refinement, based on the optimized geometries, then often achieves a superior fit to the experimental diffraction data compared with relying on experimental information alone. It also simplifies and standardizes disorder refinement. Ten example structures were analysed. It is observed that energy differences between separate disorder conformations are usually within a small energy window of RT (T = crystallization temperature). Further computations classify disorder into static or dynamic, using single experiments performed at one single temperature, and this was achieved for propionamide. |
| first_indexed | 2024-04-11T19:55:01Z |
| format | Article |
| id | doaj.art-97ae99adce184b9b80eecfe83830933b |
| institution | Directory Open Access Journal |
| issn | 2052-2525 |
| language | English |
| last_indexed | 2024-04-11T19:55:01Z |
| publishDate | 2021-03-01 |
| publisher | International Union of Crystallography |
| record_format | Article |
| series | IUCrJ |
| spelling | doaj.art-97ae99adce184b9b80eecfe83830933b2022-12-22T04:06:06ZengInternational Union of CrystallographyIUCrJ2052-25252021-03-018230531810.1107/S2052252521000531fc5050On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorderBirger Dittrich0Novartis Campus, Novartis Pharma AG, Postfach, Basel, CH-4002, SwitzerlandDistinguishing disorder into static and dynamic based on multi-temperature X-ray or neutron diffraction experiments is the current state of the art, but is only descriptive, not predictive. Here, several disordered structures are revisited from the Cambridge Crystallographic Data Center `drug subset', the Cambridge Structural Database and own earlier work, where experimental intensities of Bragg diffraction data were available. Using the molecule-in-cluster approach, structures with distinguishable conformations were optimized separately, as extracted from available or generated disorder models of the respective disordered crystal structures. Re-combining these `archetype structures' by restraining positional and constraining displacement parameters for conventional least-squares refinement, based on the optimized geometries, then often achieves a superior fit to the experimental diffraction data compared with relying on experimental information alone. It also simplifies and standardizes disorder refinement. Ten example structures were analysed. It is observed that energy differences between separate disorder conformations are usually within a small energy window of RT (T = crystallization temperature). Further computations classify disorder into static or dynamic, using single experiments performed at one single temperature, and this was achieved for propionamide.http://scripts.iucr.org/cgi-bin/paper?S2052252521000531quantum crystallographycrystal structuresdisorder refinementmolecule-in-cluster optimizations |
| spellingShingle | Birger Dittrich On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorder IUCrJ quantum crystallography crystal structures disorder refinement molecule-in-cluster optimizations |
| title | On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorder |
| title_full | On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorder |
| title_fullStr | On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorder |
| title_full_unstemmed | On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorder |
| title_short | On modelling disordered crystal structures through restraints from molecule-in-cluster computations, and distinguishing static and dynamic disorder |
| title_sort | on modelling disordered crystal structures through restraints from molecule in cluster computations and distinguishing static and dynamic disorder |
| topic | quantum crystallography crystal structures disorder refinement molecule-in-cluster optimizations |
| url | http://scripts.iucr.org/cgi-bin/paper?S2052252521000531 |
| work_keys_str_mv | AT birgerdittrich onmodellingdisorderedcrystalstructuresthroughrestraintsfrommoleculeinclustercomputationsanddistinguishingstaticanddynamicdisorder |