Massively parallel, computationally-guided design of a pro-enzyme

Abstract

The ability to confine the activity of a protein to a specific microenvironment by design would have broad-ranging applications, such as enabling cell type-specific therapeutic action by enzymes while avoiding off-target effects. While many natural enzymes are synthesized as pro-enzymes that are activated by proteolysis, it has been a difficult challenge to effectively re-design any chosen enzyme to be similarly stimulus-responsive. Here, we develop a massively parallel computational design, screening, and next-generation sequencing-based approach for pro-enzyme design. As a model system, we employ CPG2, a clinically approved enzyme that has applications in both the treatment of cancer and controlling drug (methotrexate) toxicity. Our designed pro-enzymes are inhibited up to fivefold, and their activity is restored following incubation with specific proteases expressed by various tumor cell types. Pro-enzymes exhibit significantly lower activity relative to the fully activated enzyme when evaluated in cell culture. Structural and thermodynamic characterization of pro-CPG2 enzymes provides insights into the mechanisms associated with pro-domain inhibition. The described methodology is general and should enable the design of a variety of pro-proteins for precise spatial regulation of their functions.