Natural tri- to hexapeptides self-assemble in water to amyloid beta-type fiber aggregates by unexpected alpha-helical intermediate structures

天然三肽至六肽在水中通过意想不到的α螺旋中间结构自组装形成β型淀粉样纤维聚集体。

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Abstract

Many fatal neurodegenerative diseases such as Alzheimer's, Parkinson, the prion-related diseases, and non-neurodegenerative disorders such as type II diabetes are characterized by abnormal amyloid fiber aggregates, suggesting a common mechanism of pathogenesis. We have discovered that a class of systematically designed natural tri- to hexapeptides with a characteristic sequential motif can simulate the process of fiber assembly and further condensation to amyloid fibrils, probably via unexpected dimeric α-helical intermediate structures. The characteristic sequence motif of the novel peptide class consists of an aliphatic amino acid tail of decreasing hydrophobicity capped by a polar head. To our knowledge, the investigated aliphatic tripeptides are the shortest ever reported naturally occurring amino acid sequence that can adopt α-helical structure and promote amyloid formation. We propose the stepwise assembly process to be associated with characteristic conformational changes from random coil to α-helical intermediates terminating in cross-β peptide structures. Circular dichroism and X-ray fiber diffraction analyses confirmed the concentration-dependent conformational changes of the peptides in water. Molecular dynamics simulating peptide behavior in water revealed monomer antiparallel pairing to dimer structures by complementary structural alignment that further aggregated and stably condensed into coiled fibers. The ultrasmall size and the dynamic facile assembly process make this novel peptide class an excellent model system for studying the mechanism of amyloidogenesis, its evolution and pathogenicity. The ability to modify the properties of the assembled structures under defined conditions will shed light on strategies to manipulate the pathogenic amyloid aggregates in order to prevent or control aggregate formation.

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