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Title: The tube model of proteins : simulations of protein folding and aggregation
Author: Ricchiuto, Piero
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2012
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Understanding the intrinsic properties of proteins to form structural motives such as α-helices and β-sheets is of fundamental importance with implications ranging from human disease to the design of novel nanomaterials. Prominent examples include the aggregation of proteins into amyloid fibrils which is related to Alzheimer's and Parkinson's disease and the design of peptides that can assemble into higher order materials such as a-helical fibers used as scaffolds in tissue engineering. This PhD project is focused on the uses of a generic coarse grained protein model to investigate (i) the conformational state diagram of ~polypeptides (ii) the folding free energy landscape of polypeptide chains (iii) the aggregation of proteins into amyloid fibrils, and (iv) quantitative calculation of a nucleation rate for amyloid fibril nucleation. Our results indicate the chain as responsible for triggering the α-β transition of protein. In addition the kinetics of protein folding is described with the aid of free-energy profiles that address the energetic barriers between conformational states. By sequence enabling the polypeptide model, it is possible to restrict the chain to a very specific part of the configuration space, which results in substantial simplification and smoothing of the free energy landscape as compared to the case of the corresponding homopolypeptide. Protein aggregation occurs when certain thermodynamic conditions are satisfied. However, the results presented here show that it is kinetic the finally decides if peptides start to aggregate forming highly organized fibril structures. Finally, we present a step-by-step procedure that allows a comparison between the predictions of the fibril nucleation rates obtained from the uses of existing nucleation theories and the actual quantitative calculations obtained from our molecular dynamics simulations.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available