Overcoming an optimization plateau in the directed evolution of highly efficient nerve agent bioscavengers

Abstract

Improving an enzyme's initially low catalytic efficiency with a new target substrate by an order of magnitude or two may require only a few rounds of mutagenesis and screening or selection. However, subsequent rounds of optimization tend to yield decreasing degrees of improvement (diminishing returns) eventually leading to an optimization plateau. We aimed to optimize the catalytic efficiency of bacterial phosphotriesterase (PTE) toward V-type nerve agents. Previously, we improved the catalytic efficiency of wild-type PTE toward the nerve agent VX by 500-fold, to a catalytic efficiency (kcat/KM) of 5 × 106 M-1 min-1. However, effective in vivo detoxification demands an enzyme with a catalytic efficiency of >107 M-1 min-1. Here, following eight additional rounds of directed evolution and the computational design of a stabilized variant, we evolved PTE variants that detoxify VX with a kcat/KM ≥ 5 × 107 M-1 min-1 and Russian VX (RVX) with a kcat/KM ≥ 107 M-1 min-1. These final 10-fold improvements were the most time consuming and laborious, as most libraries yielded either minor or no improvements. Stabilizing the evolving enzyme, and avoiding tradeoffs in activity with different substrates, enabled us to obtain further improvements beyond the optimization plateau and evolve PTE variants that were overall improved by >5000-fold with VX and by >17 000-fold with RVX. The resulting variants also hydrolyze G-type nerve agents with high efficiency (GA, GB at kcat/KM > 5 × 107 M-1 min-1) and can thus serve as candidates for broad-spectrum nerve-agent prophylaxis and post-exposure therapy using low enzyme doses.

Keywords: PROSS; computational design; enzyme engineering; phosphotriesterase; protein stability.