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Center for Nonlinear Studies |
The aggregation of proteins and peptides in the body is often a pathological process that an lead to debilitating diseases. Alzheimer's, Huntington's, and Parkinson's diseases, for instance, are associated with the formation of toxic oligomers and fibrillar aggregates that deposit on tissue in the body in the form of amyloid plaques. Approximately 20 different proteins, sharing low sequence and low native structure homology, are involved in amyloid diseases. There is compelling experimental evidence that amyloid fibril self-assembly is based, to a large extent, on fundamental properties of the polypeptide chain. Indeed, several experiments have shown that even nonpathogenic globular proteins can self-assemble into amyloid fibrils under partial denaturation conditions. Furthermore, fragments of aggregating peptides as well as synthetic peptides with de novo sequences, have also been shown to form amyloids in vitro.
In the first part of my talk, I will discuss the results of fully atomistic Langevin Dynamics simulations of the KFFE peptide. The KFFE peptide is a minimal model system to investigate the balance of forces involved in amyloid formation as it is one of the smallest peptides to possess two key elements that are commonly believed to contribute to aggregation, namely, an aromatic, hydrophobic core (FF) with high beta-sheet propensity and two oppositely charged terminal groups (K and E). The relative roles of the aromatic residues and oppositely charged end groups in stabilizing the earliest oligomers and the end-products of aggregation will be discussed.
In the second part, I will take a shift in perspective and introduce a novel coarse grained model for peptide aggregation and amyloid formation. I will discuss both, the effects of beta-sheet propensity on the structural features of the peptide aggregates and the parallels between uniaxial peptide aggregates and nematic liquid crystals.
In the third and final part of my talk I will introduce a coarse grained model for the folding of four helix bundle proteins, based on a binary code of generic polar and nonpolar residues. The model correctly reproduces the experimental results of a successful protein design strategy described in a series of papers by Hecht and coauthors (Review Paper: Protein Science (2004) 13: 1711-1723).
Host: Golan Bel CCS-3/CNLS