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Shape morphing of hydrogels by harnessing enzyme enabled mechanoresponse.

Kuan ZhangYu ZhouJunsheng ZhangQing LiuChristina HanenbergAhmed MourranXin WangXiang GaoYi CaoAndreas HerrmannLifei Zheng
Published in: Nature communications (2024)
Hydrogels have been designed to react to many different stimuli which find broad applications in tissue engineering and soft robotics. However, polymer networks bearing mechano-responsiveness, especially those displaying on-demand self-stiffening and self-softening behavior, are rarely reported. Here, we design a mechano-controlled biocatalytic system at the molecular level that is incorporated into hydrogels to regulate their mechanical properties at the material scale. The biocatalytic system consists of the protease thrombin and its inhibitor, hirudin, which are genetically engineered and covalently coupled to the hydrogel networks. The catalytic activity of thrombin is reversibly switched on by stretching of the hydrogels, which disrupts the noncovalent inhibitory interaction between both entities. Under cyclic tensile-loading, hydrogels exhibit self-stiffening or self-softening properties when substrates are present that can self-assemble to form new networks after being activated by thrombin or when cleavable peptide crosslinkers are constitutional components of the original network, respectively. Additionally, we demonstrate the programming of bilayer hydrogels to exhibit tailored shape-morphing behavior under mechanical stimulation. Our developed system provides proof of concept for mechanically controlled reversible biocatalytic processes, showcasing their potential for regulating hydrogels and proposing a biomacromolecular strategy for mechano-regulated soft functional materials.
Keyphrases
  • tissue engineering
  • hyaluronic acid
  • drug delivery
  • drug release
  • extracellular matrix
  • wound healing
  • machine learning
  • single molecule
  • climate change
  • deep learning