Artificial Dynamic Guest-Adaptive Hosts for Catalysts and Sensors

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Modern industrial catalysts are able to multiply the value of chemical feedstocks many times in current practice, but synthetic catalysts are unable to match the efficiency and selectivity of enzymes. Likewise, synthetic chemosensors cannot rival the sensitivity and selectivity of protein receptors. Biological systems are tuned by evolution via natural selection, allowing their function to be tuned in ways that the cleverest designer might find hard to predict. We propose to create new catalysts and sensors that are able to evolve to hone their function. The goal of this project is to create a new class of molecular containers capable of evolving to bind different guests with high affinity. This adaptation will find use in the creation of guest-specific sensors and enzyme-like catalysts, when transition-state analogues are used for templation. The ability to quickly make designer catalysts for different reactions, coupled with the ability to operate in water, could render these catalytic capsules industrially useful as green nano-reactors.