Adaptive landscape flattening allows the design of both enzyme: Substrate binding and catalytic power.

ABSTRACT: Designed enzymes are of fundamental and technological interest. Experimental directed evolution still has significant limitations, and computational approaches are a complementary route. A designed enzyme should satisfy multiple criteria: stability, substrate binding, transition state binding. Such multi-objective design is computationally challenging. Two recent studies used adaptive importance sampling Monte Carlo to redesign proteins for ligand binding. By first flattening the energy landscape of the apo protein, they obtained positive design for the bound state and negative design for the unbound. We have now extended the method to design an enzyme for specific transition state binding, i.e., for its catalytic power. We considered methionyl-tRNA synthetase (MetRS), which attaches methi

SUBMITTER: Opuu V 

PROVIDER: S-EPMC7041857 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature