Reliable and practical computational description of molecular crystal polymorphs
Reliable and practical computational description of molecular crystal polymorphs
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DOI：
10.1126/sciadv.aau3338
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发表时间：
2019-01-01
期刊：
影响因子：
13.6
通讯作者：
Tkatchenko, Alexandre
中科院分区：
文献类型：
--
作者：
Hoja, Johannes;Ko, Hsin-Yu;Tkatchenko, Alexandre
可靠的预测分子晶体的多晶型能量景观将产生深刻的洞察药物开发方面的存在和可能性，后期出现的多晶型。然而，分子晶体多晶型物的计算预测是非常具有挑战性的，由于伴随着相对自由能在1 kJ/mol permolecule内的相对自由能的构象和晶体学空间的高维性。在本研究中，我们联合收割机最成功的晶体结构采样策略和最成功的第一性原理能量排序策略的最新盲测有机晶体结构预测方法。具体来说，我们提出了一个层次的能量排名方法，旨在细化的晶体结构预测过程的最后阶段的相对稳定性。这种组合的方法为所有研究的系统提供了优异的稳定性排名，并且可以应用于具有药物重要性的分子晶体。
Reliable prediction of the polymorphic energy landscape of a molecular crystal would yield profound insight into drug development in terms of the existence and likelihood of late-appearing polymorphs. However, the computational prediction of molecular crystal polymorphs is highly challenging due to the high dimensionality of conformational and crystallographic space accompanied by the need for relative free energies to within 1 kJ/mol permolecule. In this study, we combine the most successful crystal structure sampling strategy with the most successful first-principles energy ranking strategy of the latest blind test of organic crystal structure prediction methods. Specifically, we present a hierarchical energy ranking approach intended for the refinement of relative stabilities in the final stage of a crystal structure prediction procedure. Such a combined approach provides excellent stability rankings for all studied systems and can be applied to molecular crystals of pharmaceutical importance.