PET hydrolase (PETase), which hydrolyzes polyethylene terephthalate (PET) into soluble building blocks, provides an attractive avenue for the bioconversion of plastics. Here we present the structures of a novel PETase from the PET-consuming microbe Ideonella sakaiensis in complex with substrate and product analogs. Through structural analyses, mutagenesis, and activity measurements, a substrate-binding mode is proposed, and several features critical for catalysis are elucidated.

Nature has provided a fantastic array of enzymes that are responsible for essential biochemical functions but not usually suitable for technological applications. Not content with the natural repertoire, protein engineering holds promise to extend the applications of improved enzymes with tailored properties. However, engineering of robust proteins remains a difficult task since the positive mutation library may not cooperate to reach the target function in most cases owing to the ubiquity of epistatic effects. The main demand lies in identifying an efficient path of accumulated mutations. Herein, we devised a computational strategy (greedy accumulated strategy for protein engineering, GRAPE) to improve the robustness of a PETase from Ideonella sakaiensis. A systematic clustering analysis combined with greedy accumulation of beneficial mutations in a computationally derived library enabled the redesign of a variant, DuraPETase, which exhibits an apparent melting temperature that is drastically elevated by 31 °C and a strikingly enhanced degradation toward semicrystalline poly(ethylene terephthalate) (PET) films (30%) at mild temperatures (over 300-fold). Complete biodegradation of 2 g/L microplastics to water-soluble products under mild conditions is also achieved, opening up opportunities to steer the biological degradation of uncollectable PET waste and further conversion of the resulting monomers to high-value molecules. The crystal structure revealed the individual mutation match with the design model. Concurrently, synergistic effects are captured, while epistatic interactions are alleviated during the accumulation process. We anticipate that our design strategy will provide a broadly applicable strategy for global optimization of enzyme performance.

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