Enhancing PET Degrading Enzymes: A Combinatory Approach

Yvonne Joho, Santana Royan, Alessandro T. Caputo, Sophia Newton, Thomas S. Peat, Janet M. Newman, Colin J. Jackson, Albert Ardèvol

ChemBioChem 2024 article cited by 29

importance 7/10 ai assisted Enzyme Catalysis and Immobilization plastic recycling stage: research

Plastic PET waste accumulates as a major environmental issue, and natural PET-degrading enzymes need improved efficiency for enzymatic recycling.

Enzymatic depolymerization could enable a circular plastic-waste economy and reduce environmental harm.

Machine learning was combined with structure-based rational design and ancestral sequence reconstruction to engineer a more active Combi-PETase variant.

Combi-PETase variant with melting temperature of 70 °C and optimal performance at 60 °C

Produced a more active, thermostable PETase variant, per the abstract.

Venue ChemBioChem
Published 2024
Work type article
Authors Yvonne Joho, Santana Royan, Alessandro T. Caputo, Sophia Newton, Thomas S. Peat, Janet M. Newman, Colin J. Jackson, Albert Ardèvol
Citations 29 (OpenAlex, at import time)
References 66
Model or method machine learning (no specific model named)
Organization not stated in source
Primary source https://doi.org/10.1002/cbic.202400084
Open access hybrid
Keywords PET, enzyme engineering, machine learning, plastic waste, thermal stability
7 / 10

significant — thousands to millions affected

Abstract states plastic waste is a substantial environmental issue and enzymatic PET recycling could enable a circular plastic-waste economy; engineered thermostable variant is a real but early-stage advance.

Basis: stated. The source itself states the scale. Stated scale: not stated in source. Method and limits.

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