Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.525185
Title: Computational studies to elucidate the role of proteins in the prevention of malaria
Author: Bibby, Jaclyn
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2010
Availability of Full Text:
Access through EThOS:
Access through Institution:
Abstract:
Malaria is a disease that affects half the world's population and is caused by a parasite spread by mosquito. The control of malaria relies on the use of insecticide treated nets to prevent transmission by mosquito bite. Nets alone act as poor barriers to insect bites and the insecticides used to treat the net have a role in killing the insect on contact. As the nets are in frequent contact with people, pyrethroids are the only class of insecticide recommended for use due to its low toxicity to mammals. Insecticide resistance to pyrethroids can occur in insects reducing the effectiveness of the nets to prevent transmission, and insects can become resistant to insecticides by the over expression of cytochrome P450 enzymes. P450 enzymes are a super family of heme containing enzymes involved in the detoxification of drugs and xenobiotics. This study uses computational modelling techniques to give an insight into the structures of the P450s involved in the detoxification of these insecticides. These computational studies complement experimental work and give an understanding of experimental results by giving an insight at the atomic level into the structures of these enzymes. The computational models give explanations for the observed results, but are also predictive and can be used to guide experimental studies. In this study, homology modelling and bioinformatics was used to build structural models of the P450s. These models were validated structurally to ensure that the proteins were correctly folded, docking studies were used to ensure that there was a good correlation between the experimental and computational results. A number of P450s are overexpressed in insecticide resistant mosquitoes these were studied to understand their ability to bind to pyrethroids and comparisons were made to P450s incapable of metabolism. Based on this, a fingerprint for metabolism was constructed that may be used to predict the capacity for metabolism in unknown P450s by identifying residues involved in metabolism. The models produced can be used to explain the profiles of metabolites observed to be produced by these enzymes. The studies on CYP6M2 investigate its ability to metabolise pyrethroids and in particular its metabolism pathway for deltamethrin. It was shown to metabolise deltamethrin at specific sites that can be explained by the models produced in this thesis. The models can also explain the specificity of the enzymes towards a number of fluorescent substrates by identifying the residues that have a steric influence. The models can be used to guide the development of novel pyrethroids that are resistant to metabolism. In addition, the models identified factors external to the active site that influence the metabolism of pyrethroids including its interaction with binding partners and the membrane as well as ligand access to the buried active site. Such factors explain the selectivity of enzymes for the logP of their substrates. These models were used to design probes specific to metabolising enzymes that can be used to identify novel P450s involved in insecticide resistance, and could be used to monitor resistance in insect populations. In the human host, toll like receptors are involved in sensing the malaria parasite and initiate an inflammatory response, an excessive inflammatory response can lead to severe forms of malaria. Mal has a central role in this pathway and the affect of malaria on the human host can be determined by the variant of this protein. Understanding the role of Mal can lead to the identification of targets for drugs that can modulate the immune response and prevent hyper inflammatory disorders.
Supervisor: Sutcliffe, Mike Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.525185  DOI: Not available
Share: