Hybrid materials have been found to be possessed with unique and novel properties, by superimposing the advantages of each component to provide material properties far superior to the individual constituents alone. These types of material are used throughout the field of bioengineering, and can facilitate biological interactions on both a molecular and cellular level, responding to biological and mechanical queues. With these inherent unique properties these materials provide novel platforms to help repair, replace and regenerate body tissues and function. This thesis explores the synthesis of new 'smart' hybrid hydrogels and their properties. Through the conjugation of self-assembling β-sheet peptide sequences to a naturally occurring poly (γ-glutamic acid) polymer backbone, peptide-polymer hybrid hydrogels were formed. These hybrid hydrogels were attributed with robust and tunable mechanical properties. Through the reassembly of the physical β-sheet crosslinks the hydrogels can respond to their mechanical environment, exhibiting 'self-healing' capabilities and a resistance to cyclic strain. Also, being composed entirely of natural peptide bonds they have excellent biocompatibility and are a promising platform for future tissue engineering scaffolds and biomedical applications. These hybrid hydrogels were further functionalised to detect for the activity of enzymatic biomarkers. A simple assay based on Förster resonance energy transfer was incorporated in to the hydrogel platform through the immobilisation of quantum dots modified with peptide substrates. The activity of matrix metalloproteinase-7 was targeted specifically, a marker for inflammation and immunity. This hydrogel sensing platform provides a basis for the in vivo sensing of enzymes and also, the potential to be used as a powerful tool to investigate biological processes in vitro.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:656495 |
| Date | January 2013 |
| Creators | Clarke, David |
| Contributors | Stevens, Molly; Stingelin, Natalie |
| Publisher | Imperial College London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10044/1/24728 |
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