Engineering a Non-Natural Photoenzyme for Improved Photon Efficiency

Photoenzymes are biological catalysts that use light to convert starting materials to products. These catalysts require photon absorption for each catalyst turnover, making quantum efficiency an important optimization parameter. Flavin-dependent 'ene’-reductases (EREDs) display latent photoenzymatic activity for synthetically valuable hydroalkylations; however, protein engineering has not been used to optimize this non-natural function. Here, we describe a protein engineering platform for the high throughput optimization of photoenzymes. A single round of engineering results in improved catalytic function toward the synthesis of 𝛾, 𝛿, 𝜀-lactams, and acyclic amides. Mechanistic studies indicate that key mutations can alter the enzyme's excited state dynamics, enhance its photon efficiency, and ultimately increase catalyst performance. Transient absorption spectroscopy reveals that engineered variants display dramatically decreased radical lifetimes – indicating a shift toward a concerted mechanism. Overall, this platform enables the development and optimization of photoenzymes for tailored applica-tions in chemical synthesis.