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  5. Embedded Enzyme Nanoclusters Depolymerize Polyesters via Chain-End Mediated Processive Degradation

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Preprint
English
2020

Embedded Enzyme Nanoclusters Depolymerize Polyesters via Chain-End Mediated Processive Degradation

0 Datasets

0 Files

English
2020
bioRxiv (Cold Spring Harbor Laboratory)
DOI: 10.1101/2020.04.25.052050

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Robert O. Ritchie
Robert O. Ritchie

University of California, Berkeley

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Christopher DelRe
Junpyo Kwon
Philjun Kang
+7 more

Abstract

Many bioactive elements, long perceived as non-viable for material development, are now emerging as viable building blocks to encode material lifecycle and to ensure our harmonious existence with nature. Yet, there is a significant knowledge gap on how bio-elements interface with synthetic counterparts and function outside of their native environments. Here, we show that when enzymes are dispersed as nanoclusters confined within macromolecular matrices, their reaction kinetics, pathway, and substrate selectivity can be modulated to achieve programmable polymer degradation down to repolymerizable small molecules. Specifically, when enzyme nanoclusters are dispersed in trace amount (~0.02 wt %) in polyesters, i.e. poly(caprolactone) (PCL) and poly(lactic acid) (PLA), chain-end mediated processive depolymerization can be realized, leading to scalable bioactive plastics for efficient sorting, such as recovery of precious metal filler from flexible electronics. Present studies demonstrate that when the enzyme is confined at dimensions similar to that of polymer chains, their behaviors are governed by the polymer conformation, segmental dynamic and thermal history, highlighting the importance to consider bioactive plastics differently from solution enzymology.

How to cite this publication

Christopher DelRe, Junpyo Kwon, Philjun Kang, Le Ma, Aaron Hall, Zhiyuan Ruan, Kyle Zolkin, Tim Li, Robert O. Ritchie, Ting Xu (2020). Embedded Enzyme Nanoclusters Depolymerize Polyesters via Chain-End Mediated Processive Degradation. bioRxiv (Cold Spring Harbor Laboratory), DOI: 10.1101/2020.04.25.052050.

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Publication Details

Type

Preprint

Year

2020

Authors

10

Datasets

0

Total Files

0

Language

English

Journal

bioRxiv (Cold Spring Harbor Laboratory)

DOI

10.1101/2020.04.25.052050

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