Direct Identification of Amyloid Peptide Fragments in Human α-Synuclein Based on Consecutive Hydrophobic Amino Acids.

Abstract

Formation of amyloid fibrils by misfolding α-synuclein is a characteristic feature of Parkinson’s disease, but the exact molecular mechanism of this process has long been an unresolved mystery. Identification of critical amyloid peptide fragments from α-synuclein may hold the key to decipher this mystery. Focusing on consecutive hydrophobic amino acids (CHAA) in the protein sequence, in this study we proposed a sequence-based strategy for direct identification of amyloid peptide fragments in α-synuclein. We picked out three CHAA fragments (two hexapeptides and one tetrapeptide) from α-synuclein and studied their amyloidogenic property. The thioflavin-T binding test, transmission electron microscopy, Congo red staining, and Fourier transform infrared spectroscopy revealed that although only hexapeptides could undergo amyloid aggregation on their own, extended peptide fragments based on any of the three peptides could form typical amyloid fibrils. Primary amyloidogenic fragments based on the three peptides showed synergetic aggregation behavior and could accelerate the aggregation of full-length α-synuclein. It was proved that hydrophobic interaction played a predominant role for the aggregation of these peptides and full-length α-synuclein. A central alanine-to-lysine substitution in each hydrophobic fragment completely eliminated the peptides’ amyloidogenic property, and alanine-to-lysine substitutions at corresponding sites in full-length α-synuclein also decreased the protein’s amyloidogenic potency. These findings suggested that CHAA fragments were potentially amyloidogenic and played an important role for the aggregation of α-synuclein. The identification of these fragments might provide helpful information for eventually clarifying the molecular mechanism of α-synuclein aggregation. On the other hand, our study suggested that the CHAA fragment might be a simple motif for direct sequence-based identification of amyloid peptides.