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Taylor CR, Mulvee MT, Perenyi DS, et al. Minimizing Polymorphic Risk through Cooperative Computational and Experimental Exploration. J Am Chem Soc. 2020;142(39):16668-16680doi: 10.1021/jacs.0c06749.
Taylor, C. R., Mulvee, M. T., Perenyi, D. S., Probert, M. R., Day, G. M., & Steed, J. W. (2020). Minimizing Polymorphic Risk through Cooperative Computational and Experimental Exploration. Journal of the American Chemical Society, 142(39), 16668-16680. https://doi.org/10.1021/jacs.0c06749
Taylor, Christopher R, et al. "Minimizing Polymorphic Risk through Cooperative Computational and Experimental Exploration." Journal of the American Chemical Society vol. 142,39 (2020): 16668-16680. doi: https://doi.org/10.1021/jacs.0c06749
Taylor CR, Mulvee MT, Perenyi DS, Probert MR, Day GM, Steed JW. Minimizing Polymorphic Risk through Cooperative Computational and Experimental Exploration. J Am Chem Soc. 2020 Sep 30;142(39):16668-16680. doi: 10.1021/jacs.0c06749. Epub 2020 Sep 17. PMID: 32897065; PMCID: PMC7586337.
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J Am Chem Soc. 2020 Sep 30;142(39):16668-16680. doi: 10.1021/jacs.0c06749. Epub 2020 Sep 17.

Minimizing Polymorphic Risk through Cooperative Computational and Experimental Exploration.

Journal of the American Chemical Society

Christopher R Taylor, Matthew T Mulvee, Domonkos S Perenyi, Michael R Probert, Graeme M Day, Jonathan W Steed

Affiliations

  1. Computational Systems Chemistry, School of Chemistry, University of Southampton, Southampton SO17 1NX, U.K.
  2. Department of Chemistry, Durham University, South Road, Durham DH1 3LE, U.K.
  3. Chemistry, School of Natural and Environmental Sciences, Newcastle University, Newcastle Upon Tyne NE1 7RU, U.K.

PMID: 32897065 PMCID: PMC7586337 DOI: 10.1021/jacs.0c06749

Abstract

We combine state-of-the-art computational crystal structure prediction (CSP) techniques with a wide range of experimental crystallization methods to understand and explore crystal structure in pharmaceuticals and minimize the risk of unanticipated late-appearing polymorphs. Initially, we demonstrate the power of CSP to rationalize the difficulty in obtaining polymorphs of the well-known pharmaceutical isoniazid and show that CSP provides the structure of the recently obtained, but unsolved, Form III of this drug despite there being only a single resolved form for almost 70 years. More dramatically, our blind CSP study predicts a significant risk of polymorphism for the related iproniazid. Employing a wide variety of experimental techniques, including high-pressure experiments, we experimentally obtained the first three known nonsolvated crystal forms of iproniazid, all of which were successfully predicted in the CSP procedure. We demonstrate the power of CSP methods and free energy calculations to rationalize the observed elusiveness of the third form of iproniazid, the success of high-pressure experiments in obtaining it, and the ability of our synergistic computational-experimental approach to "de-risk" solid form landscapes.

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