From Concept to Crystals via Prediction: Multi-Component Organic Cage Pots by Social Self-Sorting
From Concept to Crystals via Prediction: Multi-Component Organic Cage Pots by Social Self-Sorting
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通过预测从概念到晶体：社会自分类的多成分有机笼罐
DOI：
10.1002/ange.201909237
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发表时间：
2019
影响因子：
--
通讯作者：
Greenaway R
中科院分区：
文献类型：
--
作者：
Greenaway R
我们描述了多组分笼罐的先验计算预测和实现，从基于候选前体的分子预测开始，到使用机器人筛选的晶体结构预测和合成。这些分子是通过三位醛与三位胺和二位胺的社会自分选形成的，而不使用正交反应性或相同位置的前体。晶体结构预测表明了丰富的多晶型景观，其中存在对手性识别的总体偏好，以形成异手性而不是同手性填充，其中异手性对更有可能填充窗口到窗口以形成双组分胶囊。然后在实验晶体结构中观察到这些晶体堆积偏好。
We describe the a priori computational prediction and realization of multi‐component cage pots, starting with molecular predictions based on candidate precursors through to crystal structure prediction and synthesis using robotic screening. The molecules were formed by the social self‐sorting of a tri‐topic aldehyde with both a tri‐topic amine and di‐topic amine, without using orthogonal reactivity or precursors of the same topicity. Crystal structure prediction suggested a rich polymorphic landscape, where there was an overall preference for chiral recognition to form heterochiral rather than homochiral packings, with heterochiral pairs being more likely to pack window‐to‐window to form two‐component capsules. These crystal packing preferences were then observed in experimental crystal structures.