• Overview

    Natural enzymes are very efficient and precise in catalyzing processes in cells. This inspired us to design new enzymes, by enhancing the activity of an existing one or remodeling an enzyme to catalyze some other reactions. With promising advances in de novo protein design, directed evolution and computer aided enzyme design we have moved closer to achieve this goal. The progress on this front should provide a deeper understanding of catalysis, help in controlling what a given enzyme is doing as well as the use of specialized enzymes for key applications, including pro-drug activation, novel synthesis of biochemically relevant molecules (e.g., chiral pharmaceuticals) and more. However, the progress in enzyme design has not yet led to designer enzymes that rival native enzymes.

  • Our Focus

    It is clear that the potential of this important field can be greatly enhanced by computational approaches that actually consider the activation barriers of the reactions that are being catalyzed. Thus we have started to quantify computer-aided enzyme design by: reproducing quantitatively the observed catalytic effects of key designer enzymes by EVB simulations [1]. Using our approaches in actual enzyme design projects, including changing the action of promiscuous enzymes, improving available designer enzymes [2]. Finally, by performing successfully the enzyme designs like directed evolution in computers [3].

    Overall we are trying to develop more quantitative design concepts that will use the calculated contribution of different residues for transition state stabilization, and exploit our ability to quantify the preorganization effects. Thus we are advancing methods for early screening and further establish our quantitative ability in the final screening stages. We are developing coarse grained (CG) model that can be used as a reference potential for the calculations of the TS binding free energy and we will also developing and refining automated approaches that can simultaneously consider several mutations. While exploring the predicted power of our approaches we continue collaborating with research groups that are involved in actual enzyme design experiments.