Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.679692
Title: Multivalent biological interactions for the detection and inhibition of HIV-1 protease
Author: Herpoldt, Karla-Luise
ISNI:       0000 0004 5371 9457
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2015
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Abstract:
Several diseases including cancer and pathogen infection are mediated by protease activity. In HIV infection, the viral protease plays a central role in the virus lifecycle, which has made it a clear therapeutic target. The dominant approach for the treatment of HIV is heavily dependent on inhibitors of this enzyme, but no new drugs have reached the market since 2006. There is thus a need for new design principles for the development of anti-retroviral therapies. Traditional methods of HIV detection are also limited in their use at point-of-care in resource-limited settings due to their reliance on highly trained laboratory personnel, cold-chain transport and expensive reagents. This thesis examines the role of peptide-protein interactions for the inhibition and detection of HIV-1 protease. Phage display is used to isolate heptameric peptide sequences which interact specifically with the enzyme. These peptides are then utilised as sensors for the detection of the enzyme through Forster Resonance Energy Transfer (FRET). The inhibitory properties of the peptides, both in isolation and through multivalent conjugates are also investigated. Finally, insights into the nature of these peptide-protein interactions are explored through molecular docking and all-atom classical molecular dynamics simulations. The expression of recombinant HIV-1 protease in E. coli is also discussed. The peptide based systems described here are expected to be more stable to environmental effects than protein based therapies and it is hoped that this work will provide new pathways for the design of peptide-based therapeutics and diagnostics for protease related diseases which do not rely on traditional methods.
Supervisor: Stevens, Molly M. ; Ryan, Mary Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.679692  DOI: Not available
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