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Transferable force field for crystal structure predictions, investigation of performance and exploration of different rescoring strategies using DFT-D methods.
Broo, Anders; Nilsson Lill, Sten O.
Afiliação
  • Broo A; Pharmaceutical Technology and Development, AstraZeneca R&D Gothenburg, Pepparedsleden 1, Mölndal S-431 83, Sweden.
  • Nilsson Lill SO; Pharmaceutical Technology and Development, AstraZeneca R&D Gothenburg, Pepparedsleden 1, Mölndal S-431 83, Sweden.
Acta Crystallogr B Struct Sci Cryst Eng Mater ; 72(Pt 4): 460-76, 2016 08 01.
Article em En | MEDLINE | ID: mdl-27484369
A new force field, here called AZ-FF, aimed at being used for crystal structure predictions, has been developed. The force field is transferable to a new type of chemistry without additional training or modifications. This makes the force field very useful in the prediction of crystal structures of new drug molecules since the time-consuming step of developing a new force field for each new molecule is circumvented. The accuracy of the force field was tested on a set of 40 drug-like molecules and found to be very good where observed crystal structures are found at the top of the ranked list of tentative crystal structures. Re-ranking with dispersion-corrected density functional theory (DFT-D) methods further improves the scoring. After DFT-D geometry optimization the observed crystal structure is found at the leading top of the ranking list. DFT-D methods and force field methods have been evaluated for use in predicting properties such as phase transitions upon heating, mechanical properties or intrinsic crystalline solubility. The utility of using crystal structure predictions and the associated material properties in risk assessment in connection with form selection in the drug development process is discussed.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article