Data-Driven Directed Enzyme Evolution for Highly Strained Ring Synthesis

Evolution has generated myriad precise and efficient enzymes to assemble the molecules and materials of life with a chemical prowess no human chemist can mimic or master. Nature’s catalysts are catalytically promiscuous, i.e. enzymes can catalyze fortuitous side reactions in addition to the functions for which they have been selected in evolution. These promiscuous activities fuel the evolution of new enzymes when altered circumstances provide a fitness advantage to such innovations. The Arnold lab pioneered tools of directed evolution to exploit this catalytic promiscuity and generate enzymes that address challenges in synthetic chemistry. Notably, we have evolved hemoproteins that catalyze new-to-nature carbene and nitrene transfer reactions, including functionalizations of C─H, Si─H, and B─H bonds as well as cyclopropanations and aziridinations of unsaturated C─C bonds.  

We now propose to use this discovery to develop a modular carbene transferase platform for synthesis of highly strained and densely functionalized cyclic systems. Throughout the proposed enzyme development, we will implement state-of-the-art tools in data-driven protein engineering, including every variant sequencing (evSeq), an accessible protocol that enables unprecedented access to paired sequence-function data for every variant produced during a protein engineering campaign. This comprehensive information will advance machine-learning guided directed evolution and thereby streamline the evolution of new enzyme function, as well as provide important insight into biochemical underpinnings that accompany such evolution.