Browse by author
Lookup NU author(s): Professor Mike ProbertORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
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.
Author(s): Taylor CR, Mulvee MT, Perenyi DS, Probert MR, Day GM, Steed JW
Publication type: Article
Publication status: Published
Journal: Journal of the American Chemical Society
Year: 2020
Volume: 142
Issue: 39
Pages: 16668-16680
Print publication date: 30/09/2020
Online publication date: 08/09/2020
Acceptance date: 08/09/2020
Date deposited: 13/11/2020
ISSN (print): 0002-7863
ISSN (electronic): 1520-5126
Publisher: American Chemical Society
URL: https://doi.org/10.1021/jacs.0c06749
DOI: 10.1021/jacs.0c06749
Altmetrics provided by Altmetric
