Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.542778
Title: Investigating protein conformational change via molecular dynamics simulation
Author: Bruce, Neil John
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2011
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Abstract:
Accumulation and aggregation of the 42-residue amyloid-[beta] (A[beta]) protein fragment, which originates from the cleavage of amyloid precursor protein by beta and gamma secretase, correlates with the pathology of Alzheimer's disease (AD). Possible therapies for AD include peptides based on the A[beta] sequence, and recently identified small molecular weight compounds designed to mimic these, that interfere with the aggregation of A[beta] and prevent its toxic effects on neuronal cells in culture. Here, we use molecular dynamics simulations to compare the mode of interaction of an active (LPFFD) and inactive (LHFFD) [beta]-sheet breaker peptide with an A[beta] fibril structure from solid state NMR studies. We found that LHFFD had a weaker interaction with the fibril than the active peptide, LPFFD, from geometric and energetic considerations, as estimated by the MM/PBSA approach. Cluster analysis and computational alanine scanning identified important ligand-fibril contacts, including a possible difference in the effect of histidine on ligand-fibril [pi]-stacking interactions, and the role of the proline residue establishing contacts that compete with those essential for maintenance of the inter-monomer [beta]-sheet structure of the fibril. Our results show that molecular dynamics simulations can be a useful way to classify the stability of docking sites. These mechanistic insights into the ability of LPFFD to reverse aggregation of toxic A[beta] will guide the redesign of lead compounds, and aid in developing realistic therapies for AD and other diseases of protein aggregation. We have also performed long explicit solvent MD simulations of unliganded amyloid fibril in three putative protonation states, in order to better understand the energetic and mechanical features of the fibril receptor. Over 100 ns MD simulations, the trajectories where fibril has Glu11 and Glu22 side-chains protonated exhibit the least deviation from the initial solid state NMR structures. Free energy calculations on these rajectories suggest that the weakest fibril interface lies in the lateral rather than transverse direction and that there is little dependence on whether the lateral interface is situated at the edge or middle of the fibril. This agrees with recent reported steered molecular dynamics calculations. Secondly, in an effort to improve the ability of atomistic simulation techniques to directly resolve protein tertiary structure from primary amino acid sequence, we explore the use of a molecular dynamics technique based on swarm intelligence, called SWARM-MD, to identify the native states of two peptides, polyalanine and AEK17, as well as Trp-cage miniprotein. We find that the presence of cooperative swarm interactions significantly enhanced the efficiency of molecular dynamics simulations in predicting native conformation. However, it also is evident that the presence of outlying simulation replicas can adversely impact correctly folded replica structures. By slowly removing the swarm potential after folding simulations, the negative effect of the swarm potential can be alleviated and better agreement with experiment obtained.
Supervisor: Bryce, Richard Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.542778  DOI: Not available
Keywords: Molecular Dynamics ; Alzheimer's Disease ; Protein Conformation ; Swarm Intelligence ; Molecular Modelling ; Thermodynamics ; Computational Chemistry
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