Minimizing polymorphic risk through cooperative computational and experimental exploration,Journal of the American Chemical Society

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Minimizing polymorphic risk through cooperative computational and experimental exploration
Journal of the American Chemical Society ( IF 14.4 ) Pub Date : 2020-09-08 , DOI: 10.1021/jacs.0c06749
Christopher R Taylor ₁ , Matthew T Mulvee ₂ , Domonkos S Perenyi ₂ , Michael R Probert ₃ , Graeme M Day ₁ , Jonathan W Steed ₂

Affiliation

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.

中文翻译：

通过协同计算和实验探索最小化多态风险

我们将最先进的计算晶体结构预测 (CSP) 技术与广泛的实验结晶方法相结合，以了解和探索药物中的晶体结构，并最大限度地降低意外迟发多晶型物的风险。最初，我们证明了 CSP 的力量可以合理化获得众所周知的药物异烟肼的多晶型的困难，并表明 CSP 提供了最近获得但未解决的该药物的 III 型结构，尽管只有一种已解析的形式近 70 年。更引人注目的是，我们的盲法 CSP 研究预测了相关异烟肼存在多态性的显着风险。采用多种实验技术，包括高压实验，我们通过实验获得了前三种已知的非溶剂化晶型异烟肼，所有这些晶型都在 CSP 程序中成功预测。我们展示了 CSP 方法和自由能计算的力量，以合理化观察到的第三种形式的异烟肼的难以捉摸、获得它的高压实验的成功，以及我们协同计算实验方法“降低风险”的能力固体形式的景观。

更新日期：2020-09-08

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