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Supradynamics: Motion in cavitand complexes
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AI
DOI：10.1016/j.chempr.2026.102954.png)
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Abstract
En 中文
Supramolecular chemistry has long sought to create synthetic receptors that mimic biology’s exquisite precision, often by relying on static concepts, such as preorganization and the lock-and-key principle. This dynamic paradigm reveals that motion creates function, a principle central to bridging synthetic systems and biological processes. This perspective, however, suggests that molecular recognition is a fundamentally dynamic dance. We demonstrate that both the host and guest are not rigid entities but fluid partners in constant motion—spinning, rolling, tumbling, and breathing—to achieve a mutually adaptive fit. This paradigm shift from structure to motion is crucial because it provides a more accurate, dynamic model for how molecules truly interact, closing the gap between synthetic systems and the fluid reality of biological processes. The longer-term ambition is to advance beyond the mere construction of structures toward the programming of motion. By understanding and harnessing these coupled dynamics, researchers have designed systems to directly link molecular motion to function, exemplified by the creation of synthetic catalysts that mimic allosteric control or the development of molecular transporters operated through selective gating. Although current synthesis is outpaced by nature’s evolutionary algorithms, integrating AI and computational modeling with this dynamic perspective offers a path forward. In the long term, mastering molecular motion is foundational to advancing nanotechnology and medicine. It promises the rational design of smart, responsive materials; more effective therapeutic agents that dynamically adapt to their targets; and sophisticated molecular machines, ultimately translating the hidden dance of molecules into societal benefit.
Keywords:
Supradynamics
Molecular motion
Cavitand complexes
Molecular recognition
Dynamic systems
Journal
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19.6
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