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High-throughput discovery of organic cages and catenanes using computational screening fused with robotic synthesis

机译:高通量发现有机笼和链烷烃采用计算机合成与计算机筛选融合

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摘要

Supramolecular synthesis is a powerful strategy for assembling complex molecules, but to do this by targeted design is challenging. This is because multicomponent assembly reactions have the potential to form a wide variety of products. High-throughput screening can explore a broad synthetic space, but this is inefficient and inelegant when applied blindly. Here we fuse computation with robotic synthesis to create a hybrid discovery workflow for discovering new organic cage molecules, and by extension, other supramolecular systems. A total of 78 precursor combinations were investigated by computation and experiment, leading to 33 cages that were formed cleanly in one-pot syntheses. Comparison of calculations with experimental outcomes across this broad library shows that computation has the power to focus experiments, for example by identifying linkers that are less likely to be reliable for cage formation. Screening also led to the unplanned discovery of a new cage topology—doubly bridged, triply interlocked cage catenanes.
机译:超分子合成是组装复杂分子的强大策略,但是要通过有针对性的设计来实现这一目标具有挑战性。这是因为多组分组装反应具有形成多种产品的潜力。高通量筛选可以探索广阔的合成空间,但是盲目使用时效率低下且不雅观。在这里,我们将计算与机器人合成相融合,以创建一个混合发现工作流程,以发现新的有机笼分子,并进而发现其他超分子系统。通过计算和实验对总共78种前体组合进行了研究,最终形成了33个笼式合成的笼子。在这个广泛的数据库中,将计算结果与实验结果进行比较表明,计算具有集中实验的能力,例如,通过识别不太可能可靠形成笼子的连接子。筛选还导致计划外的新笼形拓扑结构的发现,即双桥,三重互锁笼形链环。

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