An in silico approach to highlight relationships between a techno-functional property of a dairy matrix and a peptide profile

Food products are complex matrices. They contain molecules from several families that interact with each other to generate specific structures and functionalities. These molecules may include proteins and peptides resulting from protein hydrolysis, e.g. in cheese. It is still difficult to establish a clear relationship between a pool of peptides and their techno-functionalities such as emulsifying, foaming, gelling or even texture properties within a complex matrix. Among the data usually known, there is the degree of hydrolysis that provides information about the average size of the peptides formed. A high degree of hydrolysis induces the production of a pool of small-size peptides (less than 20 amino acids). Advances in identification methods have made the identification of peptides present in food products possible. The size, charge, hydropathy index and isoelectric point of the peptide, as well as its secondary structure, can be calculated on the basis of the peptide sequence. The aim of this study was to determine which physicochemical and structural characteristics of peptides are involved in the cheese stretchability. This work is a re-evaluation, using multivariate exploratory analysis, of the experimental data obtained from a former study (Sadat-Mekmene et al., 2013) in which one typical functionality criterion of Swiss-type cheese ( stretchability) was measured and peptides were identified. This methodology, based on Principal Component Analysis and Correspondence Analysis, is one way to establish a relationship between peptide characteristics and their techno-functional property within a complex dairy matrix. This statistical approach showed that the peptides predominantly involved in cheese stretchability were a mixture of both hydrophobic and hydrophilic peptides and that they are large enough to interact with each other and with native proteins. This approach could be applied to better understand the impact of peptides on various food matrices and food techno-functionalities. (C) 2014 Elsevier B.V. All rights reserved.