Evidence map›Paper›PMID 42823503›Full record

ReviewNature chemical biology2026

Advances in amidases and urethanases as depolymerization biocatalysts.

Thomas Bayer, Hannes Meinert, Ren Wei, Uwe T Bornscheuer

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature chemical biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Thomas BayerDepartment of Biotechnology and Enzyme Catalysis, Institute of Biochemistry, University of Greifswald, Greifswald, Germany. thomas.bayer@unibe.ch.
Hannes MeinertDepartment of Biotechnology and Enzyme Catalysis, Institute of Biochemistry, University of Greifswald, Greifswald, Germany.ORCID http://orcid.org/0000-0001-6545-5047
Ren WeiDepartment of Biotechnology and Enzyme Catalysis, Institute of Biochemistry, University of Greifswald, Greifswald, Germany.ORCID http://orcid.org/0000-0003-3876-1350
Uwe T BornscheuerDepartment of Biotechnology and Enzyme Catalysis, Institute of Biochemistry, University of Greifswald, Greifswald, Germany. uwe.bornscheuer@uni-greifswald.de.ORCID http://orcid.org/0000-0003-0685-2696

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 953214
6 · The paper itself

Abstract

Stable chemical bonds as well as noncovalent interactions define the properties of industrial chemicals and materials, including polyesters such as polyethylene terephthalate (PET), polyamides (nylons) and polyurethanes. The resistance of plastics to hydrolysis contributes to the global issues of waste accumulation and environmental pollution. Recently identified metagenomic enzymes act on highly stable ester, amide and carbamate bonds in small molecules as well as pretreated polymeric materials. However, depolymerization activities, particularly for nylons and polyurethanes, remain too low to facilitate the efficient treatment of plastic waste. This Perspective highlights the natural diversity of different hydrolase superfamilies suitable for deconstructing synthetic polymers and examines their catalytic features. We also discuss strategies for discovering biocatalysts and tailoring their properties by protein engineering-both assisted by bioinformatics and (ultra)high-throughput screening tools. The combination of these approaches and thorough process analyses will be required to advance hydrolase-based depolymerization of plastics beyond the current recycling schemes for PET.

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.