Streamlined Identification of Metallopeptides for Intracellular Catalysis Using Positionally-Addressable Combinatorial Libraries

The discovery and development of artificial catalysts to carry out biorthogonal reactions in living cells is a primary goal at the interface of Chemistry and Biology. Current approaches rely on time-consuming trial-and-error methods that often fail to yield an optimal catalyst. In contrast, we show that positionally addressable combinatorial libraries (SPOT libraries) provide a significant advantage for the efficient identification of novel catalytic metallopeptides. Using these libraries, we were able to rapidly identify catalytic β-hairpin palladopeptides capable of promoting efficient depropargylation reactions, even in challenging intracellular environments.