Minimizing Polymorphic Risk through Cooperative Computational and Experimental Exploration.

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 experimen

SUBMITTER: Taylor CR 

PROVIDER: S-EPMC7586337 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature