Iterative computational and rational design generates diverse PET hydrolases for plastic depolymerization
Year: 2026
Type: article
Abstract: Evolutionary relationships among homologous enzymes can be leveraged to introduce large numbers of amino acid substitutions for improved functional properties. Here, we combine evolution-informed design (EVdesign) with rational design to engineer improved poly(ethylene terephthalate) (PET) hydrolases (PETases). Designs derived from multiple PETases reveal strong parent-dependent differences in success and performance, with Thermobifida fusca TfCut2 emerging as the most design-amenable scaffold. Increasing sequence diversification reduces the number of active enzymes but broadens performance variance, enabling discovery of high-performing outliers. Four rational mutations overcome a thermostability bottleneck in TfCut2 and this variant provides a robust scaffold for iterative EVdesign, which further improves activity. Overall, we experimentally test 603 designs from eight parent PETases. More than 400 variants containing 12-68 substitutions were able to depolymerize PET, nearly all outperforming their parent enzymes, and many approach benchmark LCC-ICCG performance in partial conversion assays. These results establish EVdesign as a robust strategy for generating diverse, high-activity enzymes.
Source: Nature Communications
Authors: Brenna Norton-Baker, Benjamin Fram, Nicole N. Thadani, Evan Komp, Yang Su, Olateju O. Storment, Natasha P. Murphy, Samuel Lim, Erika Erickson, Nathan Rollins, Japheth E. Gado, Courtney A. Shearer, Irimpan I. Mathews, Ian Truebridge, Maria Llases, Christopher D. Bahl, Ritimukta Sarangi, Debora S. Marks, John E. McGeehan, Chris Sander, Gregg T. Beckham, Nicholas P. Gauthier
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $6,990
OpenAlex ID: W7225154368