Abstract

In this work the identification of peptides derived from quinoa proteins which could potentially self-assemble, and form hydrogels was carried out with TANGO, a statistical mechanical based algorithm that predicts β-aggregate propensity of peptides. Peptides with the highest aggregate propensity were subjected to gelling screening experiments from which the most promising bioactive peptide with sequence KIVLDSDDPLFGGF was selected. The self-assembling and hydrogelation properties of the C-terminal amidated peptide (KIVLDSDDPLFGGF-NH2) were studied. The effect of concentration, pH, and temperature on the secondary structure of the peptide were probed by circular dichroism (CD), while its nanostructure was studied by transmission electron microscopy (TEM) and small-angle neutron scattering (SANS). Results revealed the existence of random coil, α-helix, twisted β-sheet, and well-defined β-sheet secondary structures, with a range of nanostructures including elongated fibrils and bundles, whose proportion was dependant on the peptide concentration, pH, or temperature. The self-assembly of the peptide is demonstrated to follow established models of amyloid formation, which describe the unfolded peptide transiting from an α-helix-containing intermediate into β-sheet-rich protofibrils. The self-assembly is promoted at high concentrations, elevated temperatures, and pH values close to the peptide isoelectric point, and presumably mediated by hydrogen bond, hydrophobic and electrostatic interactions, and π-π interactions (from the F residue). At 15 mg/mL and pH 3.5, the peptide self-assembled and formed a self-supporting hydrogel exhibiting viscoelastic behaviour with G' (1 Hz) ~2300 Pa as determined by oscillatory rheology measurements. The study describes a straightforward method to monitor the self-assembly of plant protein derived peptides; further studies are needed to demonstrate the potential application of the formed hydrogels in food and biomedicine.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call