Computational design of serine hydrolases

Abstract

Nature’s enzymes are exceptionally powerful catalysts, exerting dramatic rate accelerations and exquisite control over a remarkable variety of chemical transformations. Since their initial discovery and characterization, the ability to generate artificial enzymes for chemical reactions involved in industrial processes, chemical synthesis, and therapeutic applications has been of considerable interest. Despite decades of effort, artificial enzymes continue to display lower catalytic activities than their native counterparts, even for well-understood model reactions. Here, we present a novel and general approach to computational enzyme design utilizing recent advances in tailored protein scaffold generation and active site conformational ensemble prediction. As a proof of concept, we have applied this method to the design of esterases that utilize the serine hydrolase enzymatic mechanism. Despite a deep understanding of the mechanism amassed through decades of study, previous attempts to design esterases acting through this mechanism have failed. To our knowledge, the designs made using our approach represent the first examples of accurately designed, de novo serine hydrolases spanning folds not found in natural hydrolases and exhibiting catalytic efficiencies on par with hydrolases in nature that act on similar substrates. We believe our approach will not only enable the design of industrially relevant serine hydrolases but also be broadly applicable to accelerating a wider array of chemical reactions, including ones that do not occur in nature.