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The human islet amylin polypeptide is produced along with insulin by pancreatic islets. Under some circumstances, amylin can aggregate to form amyloid fibrils, whose presence in pancreatic cells is a common pathological feature of Type II diabetes. A growing body of evidence indicates that small, early stage aggregates of amylin are cytotoxic. A better understanding of the early stages of the amylin aggregation process and, in particular, of the nucleation events leading to fibril growth could help identify therapeutic strategies. Recent studies have shown that, in dilute solution, human amylin can adopt an α-helical conformation, a β-hairpin conformation, or an unstructured coil conformation. While such states have comparable free energies, the β-hairpin state exhibits a large propensity towards aggregation. In this work, we present a detailed computational analysis of the folding pathways that arise between the various conformational states of human amylin in water. A free energy surface for amylin in explicit water is first constructed by resorting to advanced sampling techniques. Extensive transition path sampling simulations are then employed to identify the preferred folding mechanisms between distinct minima on that surface. Our results reveal that the α-helical conformer of amylin undergoes a transformation into the β-hairpin monomer through one of two mechanisms. In the first, misfolding begins through formation of specific contacts near the turn region, and proceeds via a zipping mechanism. In the second, misfolding occurs through an unstructured coil intermediate. The transition states for these processes are identified. Taken together, the findings presented in this work suggest that the inter-conversion of amylin between an α-helix and a β-hairpin is an activated process and could constitute the nucleation event for fibril growth. [ABSTRACT FROM AUTHOR]

A growing body of experimental evidence indicates that the interaction between amyloid β peptide and lipid bilayer membranes plays an important role in the development of Alzheimer disease. Recent experimental evidence also suggests that trehalose, a simple disaccharide, reduces the toxicity of amyloid β peptide. Molecular simulations are used to examine the effect of trehalose on the conformational stability of amyloid β peptide in aqueous solution and its effect on the interaction between amyloid β peptide and a model phospholipid bilayer membrane. It is found that, in aqueous solution, the peptide exhibits a random coil conformation but, in the presence of trehalose, it adopts an alpha helical conformation. It is then shown that the insertion of amyloid β peptide into a membrane is more favorable when the peptide is folded into an α-helix than in a random coil conformation, thereby suggesting that trehalose promotes the insertion of α-helical amyloid β into biological membranes. [ABSTRACT FROM AUTHOR]

Long polyglutamine chains have been associated with a number of neurodegenerative diseases. These include Huntington’s disease, where expanded polyglutamine (PolyQ) sequences longer than 36 residues are correlated with the onset of symptoms. In this paper we study the folding pathway of a 54-residue PolyQ chain into a β-helical structure. Transition path sampling Monte Carlo simulations are used to generate unbiased reactive pathways between unfolded configurations and the folded β-helical structure of the polyglutamine chain. The folding process is examined in both explicit water and an implicit solvent. Both models reveal that the formation of a few critical contacts is necessary and sufficient for the molecule to fold. Once the primary contacts are formed, the fate of the protein is sealed and it is largely committed to fold. We find that, consistent with emerging hypotheses about PolyQ aggregation, a stable β-helical structure could serve as the nucleus for subsequent polymerization of amyloid fibrils. Our results indicate that PolyQ sequences shorter than 36 residues cannot form that nucleus, and it is also shown that specific mutations inferred from an analysis of the simulated folding pathway exacerbate its stability. [ABSTRACT FROM AUTHOR]

The free energy surfaces of a wide variety of systems encountered in physics, chemistry, and biology are characterized by the existence of deep minima separated by numerous barriers. One of the central aims of recent research in computational chemistry and physics has been to determine how transitions occur between deep local minima on rugged free energy landscapes, and transition path sampling (TPS) Monte-Carlo methods have emerged as an effective means for numerical investigation of such transitions. Many of the shortcomings of TPS-like approaches generally stem from their high computational demands. Two new algorithms are presented in this work that improve the efficiency of TPS simulations. The first algorithm uses biased shooting moves to render the sampling of reactive trajectories more efficient. The second algorithm is shown to substantially improve the accuracy of the transition state ensemble by introducing a subset of local transition path simulations in the transition state. The system considered in this work consists of a two-dimensional rough energy surface that is representative of numerous systems encountered in applications. When taken together, these algorithms provide gains in efficiency of over two orders of magnitude when compared to traditional TPS simulations. [ABSTRACT FROM AUTHOR]