Enzyme Enhancement Through Computational Stability Design Targeting NMR-Determined Catalytic Hotspots.

ABSTRACT: Enzymes are the quintessential green catalysts, but realizing their full potential for biotechnology typically requires improvement of their biomolecular properties. Catalysis enhancement, however, is often accompanied by impaired stability. Here, we show how the interplay between activity and stability in enzyme optimization can be efficiently addressed by coupling two recently proposed methodologies for guiding directed evolution. We first identify catalytic hotspots from chemical shift perturbations induced by transition-state-analogue binding and then use computational/phylogenetic design (FuncLib) to predict stabilizing combinations of mutations at sets of such hotspots. We test this approach on a previously designed de novo Kemp eliminase, which is already highly optimized in terms o

SUBMITTER: Gutierrez-Rus LI 

PROVIDER: S-EPMC12151457 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature