Design and Evolution of Enzymes for the Morita-Baylis-Hillman Reaction

Abstract

The combination of computational design and directed evolution is a powerful strategy for the creation of enzymes with new functions, which has so far delivered enzymes for a small number of model reactions. Here, we show that new catalytic mechanisms can be engineered into proteins to accelerate more challenging chemical transformations for which no natural enzymes or catalytic antibodies are known. In an initial study, evolutionary optimization of a primitive design gave rise to an efficient and enantioselective MBHase (BH32.14) for the Morita-Baylis-Hillman reaction. Computational, crystallographic and biochemical studies reveal a sophisticated mechanism comprising a His23 nucleophile paired with a flexible Arg124, that shuttles between conformational states to stabilize multiple oxyanion intermediates. The catalytic arginine serves as a genetically encodable surrogate of small molecule thioureas which promote the MBH and other reactions in organic synthesis. In a more recent study, we have exploited an expanded genetic code for the development of a highly efficient MBHase, BH(MeHis)1.8. Replacement of the catalytic histidine in a BH32 scaffold with a N-methylhistidine (MeHis23) nucleophile, has provided a unique opportunity to study how evolutionary trajectories are influenced by the introduction of non-canonical catalytic elements. Laboratory evolution has led to an extensively remodelled active site and catalytic mechanism in which the critical arginine of BH32.14 has been abandoned. Instead, a Glu26 residue has emerged that mediates the rate-limiting proton transfer step in BH(MeHis)1.8. Interestingly, replacement of the MeHis nucleophile with histidine affords only a modest reduction in kcat, however, analysis along the whole evolutionary trajectory highlights the importance of the non-canonical nucleophile in unlocking the new mechanistic pathway. These studies demonstrate how elaborate catalytic devices can be built from scratch to promote demanding multi-step processes, and how the introduction of small perturbations to the catalytic machinery of designed enzymes can lead to vastly different evolutionary outcomes.

Date of Award	1 Aug 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Anthony Green (Supervisor) & Sarah Lovelock (Supervisor)