PETase learns from LCC: reprogramming enzymatic reactivity with probability-based simulations

Despite significant interest in enzymatic plastic degradation, the catalytic performance of currently available enzymes remains limited under industrially relevant conditions. Addressing this limitation requires approaches that can systematically identify the molecular features controlling catalytic efficiency and use this information to guide targeted enzyme engineering. Here, we simulate and contrast the catalytic activity of two enzymes, PETase and LCC ICCG , which are receiving considerable attention for their ability to degrade polyethylene terephthalate and related polyesters. These two enzymes have different properties. PETase has a more accessible active site but a moderate catalytic efficiency and thermal stability. LCC ICCG exhibits superior catalytic efficiency but requires higher temperatures to operate efficiently, associated with a less accessible active site. Using a new, efficient sampling method based on the committor function, combined with electronic and structural analysis, we characterize in great detail how both enzymes operate, identify the molecular reasons for their different catalytic efficiencies, and translate these mechanistic insights into the rational design of a double mutation (W130H and I179V) that significantly enhances PETase activity. This alters PETase catalytic behavior, promoting a mechanism similar to that of LCC ICCG , thus combining the best of the two worlds and potentially enabling efficient catalysis at lower temperatures.