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.

Introduction of innovative biocatalytic processes offers great promise for applications in green chemistry. However, owing to limited catalytic performance, the enzymes harvested from nature's biodiversity often need to be improved for their desired functions by time-consuming iterative rounds of laboratory evolution. Here we describe the use of structure-based computational enzyme design to convert Bacillus sp. YM55-1 aspartase, an enzyme with a very narrow substrate scope, to a set of complementary hydroamination biocatalysts. The redesigned enzymes catalyze asymmetric addition of ammonia to substituted acrylates, affording enantiopure aliphatic, polar and aromatic β-amino acids that are valuable building blocks for the synthesis of pharmaceuticals and bioactive compounds. Without a requirement for further optimization by laboratory evolution, the redesigned enzymes exhibit substrate tolerance up to a concentration of 300 g/L, conversion up to 99%, β-regioselectivity >99% and product enantiomeric excess >99%. The results highlight the use of computational design to rapidly adapt an enzyme to industrially viable reactions.