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Mechanism-Based Design of Efficient PET Hydrolases

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Wei, Ren, von Haugwitz, Gerlis, Pfaff, Lara, Mican, Jan, Badenhorst, Christoffel P. S., Liu, Weidong, Weber, Gert, Austin, Harry P., Bednar, David, Damborsky, Jiri, Bornscheuer, Uwe T.·2022·ACS Catalysis

DOI 10.1021/acscatal.1c05856

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Abstract

Polyethylene terephthalate (PET) is the most widespread synthetic polyester, having been utilized in textile fibers and packaging materials for beverages and food, contributing considerably to the global solid waste stream and environmental plastic pollution. While enzymatic PET recycling and upcycling have recently emerged as viable disposal methods for a circular plastic economy, only a handful of benchmark enzymes have been thoroughly described and subjected to protein engineering for improved properties over the last 16 years. By analyzing the specific material properties of PET and the reaction mechanisms in the context of interfacial biocatalysis, this Perspective identifies several limitations in current enzymatic PET degradation approaches. Unbalanced enzyme-substrate interactions, limited thermostability, and low catalytic efficiency at elevated reaction temperatures, and inhibition caused by oligomeric degradation intermediates still hamper industrial applications that require high catalytic efficiency. To overcome these limitations, successful protein engineering studies using innovative experimental and computational approaches have been published extensively in recent years in this thriving research field and are summarized and discussed in detail here. The acquired knowledge and experience will be applied in the near future to address plastic waste contributed by other mass-produced polymer types (e.g., polyamides and polyurethanes) that should also be properly disposed by biotechnological approaches.

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An archaeal lid-containing feruloyl esterase degrades polyethylene terephthalate
(2023) · doi:10.1038/s42004-023-00998-z · Cited by 79
Thermophilic Carboxylesterases from Hydrothermal Vents of the Volcanic Island of Ischia Active on Synthetic and Biobased Polymers and Mycotoxins
(2023) · doi:10.1128/aem.01704-22 · Cited by 25
Insights into the Catalytic Activity of a Metagenome-Derived Urethanase
Świderek, K., Arafet, K., de Sousa Batista, V., Grajales-Hernández, D., López-Gallego, F., & Moliner, V. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.5c13147 · Cited by 4

See all 284

Authors: Wei, R., von Haugwitz, G., Pfaff, L., Mican, J., Badenhorst, C. P. S., Liu, W., Weber, G., Austin, H. P., Bednar, D., Damborsky, J., & Bornscheuer, U. T.
Venue: ACS Catalysis
Publisher: American Chemical Society (ACS)
Published: 2022-02-28
Volume: 12
Issue: 6
Pages: 3382-3396
ISSN: 2155-5435 (ISSN-L)
DOI: 10.1021/acscatal.1c05856
OpenAlex: W4214674682
Cited by: 284
References: 169
FWCI: 15.40
Type: journal article
Language: en
Open access: hybrid
Licence: creativecommons.org/licenses/by-nc-nd/4.0/ (unspecified)
Funders: Ministerstvo ?kolstv?, Ml?de?e a Telov?chovy (CZ.02.1.01/0.0/0.0/16_026/0008451)
H2020 Industrial Leadership (870294, 953214)
Horizon 2020 Framework Programme (857560)
Alexander von Humboldt-Stiftung

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.

Mechanism-Based Design of Efficient PET Hydrolases

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