Investigation of interactions responsible for amyloid formation in various diseases
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In various amyloidic pathological diseases, such as type II diabetes, Alzheimerâ s disease, Parkinsonâ s disease, Creutzfeld-Jakob disease, progression and cell death correlate with the accumulation of these peptide plaques. Amyloids are highly ordered, stable, insoluble polypeptide aggregates with characteristic cross-beta sheet structure, formed by self-assembly of disordered and misfolded peptides and proteins governed by noncovalent interactions. Numerous studies indicate that aromatic amino acids and metal ions play important roles in amyloid formation; however, despite intensive research, these roles are not understood and the nature of the toxicity is also unclear. As proposed, studies of these interactions will determine the roles of various types of noncovalent interactions, particularly aromatic ones, and metal-ion interactions in the formation of amyloids. A deep understanding of the roles of these noncovalent and metal ion interactions can lead to drugs to control and prevent the toxic effects related to amyloid formation. Computational studies such as proposed here have been shown to be very successful in drug discovery. By computational chemical approaches, this study will examine noncovalent aromatic-aromatic interactions, as well as noncovalent interactions of aromatic rings with other groups from surrounding peptide residues like CH/pi, and CH/O interactions. Importance of metal ions will be examined by studying their interactions with peptides, and interactions among various peptide groups bound to metal ions. Comparison of noncovalent interactions in amyloid structures with those in correctly folded proteins will determine possible difference in interactions in these two types of structures that lead to misfolding. This study will include investigations of inhibitors of toxicity related to amyloid formation. The computational approaches will be extended by experimental studies on a few important amyloid-forming proteins, such as A-beta, amylin, and a-synuclein, which are involved in Alzheimerâ s disease, diabetes, and Parkinsonâ s disease, respectively. Therefore, this study will rely on both experimental data and calculations on model systems. In addition, two experimental collaborators, who have been investigating drugs to prevent these diseases, have agreed to share their preliminary results, so that the proposed computational techniques will help them design better drugs. The overarching goal is to gain knowledge in controlling and preventing the toxic effects of amyloid formation that can alleviate these pathological diseases.