Engineering V-type nerve agents detoxifying enzymes using computationally focused libraries.

VX and its Russian (RVX) and Chinese (CVX) analogues rapidly inactivate acetylcholinesterase and are the most toxic stockpile nerve agents. These organophosphates have a thiol leaving group with a choline-like moiety and are hydrolyzed very slowly by natural enzymes. We used an integrated computational and experimental approach to increase Brevundimonas diminuta phosphotriesterase's (PTE) detoxification rate of V-agents by 5000-fold. Computational models were built of the complex between PTE and V-agents. On the basis of these models, the active site was redesigned to be complementary in shape to VX and RVX and to include favorable electrostatic interactions with their choline-like leaving group. Small libraries based on designed sequences were constructed. The libraries were screened by a direct assay for V-agent detoxification, as our initial studies showed that colorimetric surrogates fail to report the detoxification rates of the actual agents. The experimental results were fed back to improve the computational models. Overall, five rounds of iterating between experiment and model refinement led to variants that hydrolyze the toxic SP isomers of all three V-agents with kcat/KM values of up to 5 × 10(6) M(-1) min(-1) and also efficiently detoxify G-agents. These new catalysts provide the basis for broad spectrum nerve agent detoxification.