Quantitative computer-aided studies of artificial and enantioselective enzymes.

摘要

A fundamental challenge in biotechnology and in biochemistry is an ability to design effective enzymes. Despite a gradual progress on this front, most of the advances have been made by placing the reacting fragments in the proper places rather than by optimizing the environment preorganization, which is the key factor in enzyme catalysis. Improving the preorganization and assessing the effectiveness of different design options requires the ability to calculate the actual catalytic effect. Current work explores the computer-aided refinement of catalytic activities (Kemp Eliminase artificial constructs and catalytic antibodies) and enantioselectivities (stereoselective Candida antarctica Lipase A enzymes) using the empirical valence bond as the main screening tool. The observed absolute catalytic effect and the effect of directed evolution experiments are reproduced and analyzed. The following refinement procedure located the mutation sites with increased catalytic activities and selectivities which have been tested experimentally. Those predictions provide a broad avenue for the design of novel catalysts. With this in mind, our approach provides a quantitative understanding of the catalytic effect of the various enzyme constructs and the results of directed evolution experiments. Furthermore, our technique provides the ability to locate the effective mutations that can increase kcat by refining the electrostatic preorganization of the protein environment, which allows us to refine and develop more efficient catalysts.