Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490938
Title: Computational studies of protein structure and evolution in the living cell
Author: Jefferys, Benjamin Richard
ISNI:       0000 0001 3589 7776
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2008
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Abstract:
This thesis describes a new protein structure model which is designed to enable the study of protein folding, evolution and the impact of cellular effects. It is fast, and therefore can be used in large-scale studies where thousands of folding simulations are necessary. It is intuitive and based upon physical concepts, and therefore can incorporate cellular effects quickly and easily. It is shown to have a predictive ability which ranks it amongst the world's best template-free structure prediction tools, and so results of studies using the model have some biological significance. The model is based upon Langevin dynamics, an established method for simulating classical mechanics. New models for several of the physicochemical effects known to be important in protein folding are developed. The implicit solvent model of the Langevin is enhanced such that solvent does not affect buried parts of a protein, and is adapted to bring about hydrophobic collapse. A new hydrogen bonding model ensures realistic association of strands into sheets. A new sidechain model brings some of the benefits of all-atom modelling to a reduced, simplified model. The model is compared to the best fragment folding method from CASP 7, and found to equal or exceed predictions from Rosetta for six of the twelve template-free targets. It is used to study the impact of two cellular effects upon protein folding. Cotranslational folding has little effect on the similarity to the known native of the first compact structures found. Macromolecular crowding destroys protein folding capabilities beyond the maximum level of crowding found in the cell. The model is currently being trialled in CASP 8 and will be developed in the future to enhance its structure prediction ability and become a useful new tool for biochemistry.
Supervisor: Not available Sponsor: Not available
Qualification Name: University of London, 2008 Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.490938  DOI: Not available
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