Self-assembly of amyloid peptides for the synthesis of functional nanobiomaterials

Abstract

The self-assembly of bioorganic molecules, which are ubiquitous in nature, is an attractive route for fabricating functional supramolecular architectures and facilitates the organization of highly ordered nanostructures from molecular building blocks through the combination of noncovalent interactions including hydrogen bonds, electrostatic interactions, π-π stacking, hydrophobic, and dipole-dipole interactions. In particular, the self-assembly of an aromatic dipeptide consisting of two covalently linked phenylalanine units (i.e., diphenylalanine, FF), which is a key structural motif in the Alzheimer’s β-amyloid polypeptides, serves as not only a hallmark of many protein mispolding disease such as Alzheimer’s, but also an excellent model for synthesis of functional nanomaterials because of the unique properties of peptides, such as functional flexibility and molecular recognition capability. In this thesis, the self-assembly of Alzheimer’s β-amyldoi peptide and synthesis of functional nanobiomaterials through self-assebmly of diphenylalanine peptides is studied from the viewpoint of materials science. Chapter 1 deals with the development of efficient analytical system for the dissociation and clearance of Alzheimer’s Aβ aggregates in vitro. When we applied the microfluidic platform to the clearance of metal ion-induced Aβ aggregates by different types of metal chelators, we found that DFO possessed a high capacity for the clearance of Fe3+-induced Aβ aggregates. We further investigated morphological and conformational changes of destabilized Aβ removed from preformed Aβ aggregates and Aβ deposits remaining within the microchannels both before and after the microfluidic clearance treatment. The ratio ofβ -sheet to α-helix of Aβ deposits within microchannels significantly decreased after the clearance treatment. These results suggest that the microfluidics-based clearance assay system has a potential to become a platform for efficient analysis of multiple envir...