Insight into the structure/function relationship in amphipathic, α-helical peptide emulsifiers: A study of a highly potent peptide emulsifier derived from potato storage proteins and its natural isoforms.

Peptide emulsifiers derived from plant proteins are gathering growing interest as green and sustainable replacements of chemical additives in food. Potato (Solanum tuberosum) is one of the most important crops for both human consumption and industrial processing. Globally, the annual production of potato starch exceeds 3.000.000MT with more than 200.000MT of potato protein isolated as a side-stream, providing an enormous source of raw protein. The direct isolation of food-grade protein is in many cases regarded as cost-ineffective. Nevertheless, potato proteins can be source of valuable bioactive peptides.
Recently, we demonstrated using amphiphilicity-based bioinformatic prediction to identify peptide emulsifiers embedded in potato proteins (manuscripts submitted). Amongst the predicted peptides, especially one (γ1), derived from the storage protein patatin, stood out with exceptional emulsifying activity in vitro. Although patatin is the most abundant protein in potatoes, it is, however, not a single protein, but a family of highly homologous isoforms.
Using buttom-up proteomics in combination with multiple sequence alignment and in silico digestion, we identified several γ1 variants. The variants consist of both full-length isoforms with single amino acid substitutions as well as tryptic variants/truncations from different isoforms. The emulsifying activity of the γ1 variants was investigated by drop tensiometry and physical stability of the emulsions was assayed by measuring zeta potential and droplet size distribution during storage. The emulsifying activity was correlated with the predicted activity by bioinformatics. Furthermore, the interfacial conformation of the peptides was investigated by SRCD and supplemented by NMR for selected peptides.
Based on the results from this study, we are able to i) evaluate the full potential of using γ1 variants as peptide emulsifier in food; ii) provide novel insight on the structure/function relationship of amphipathic, α-helical peptide emulsifiers; and iii) further validate our predictive algorithm and thereby highlighting the potential of using bioinformatic prediction of food functionality.