Bioinformatic Analysis of Changes in the Peptide Profile of Dairy Proteins During Storage

Introduction: Enzymatic processes occurring in dairy products during storage can lead to changes in protein composition, affecting products’ quality. Key players in these changes include endogenous enzymes, such as plasmin, and bacterial proteases like the heat stable protease from Pseudomonas LBSA1. The application of bioinformatic methods enables the modeling of protein hydrolysis and prediction of peptide formation with specific properties (e.g., organoleptic characteristics, bioactivity, molecular weight, amino acid sequence).

Purpose: To evaluate changes in the peptide profiles of β-CN, αs1-CN, αs2-CN, and κ-CN caseins during simulated hydrolysis by plasmin and the heat stable bacterial protease Pseudomonas LBSA1.

Materials and Methods: Casein sequences were analyzed using the UniProt database. Hydrolysis was modeled using BIOPEP-UWM (for plasmin) and regular expressions in RStudio (for Pseudomonas LBSA1). The degree of hydrolysis (DH) was calculated as the ratio of cleaved peptide bonds to the total possible bonds in the protein. Peptide sequences were analyzed using the “stringr” library in RStudio. Bitter and antioxidant peptides were identified using the BIOPEP-UWM database. Molecular weight and isoelectric point data were obtained via the “Peptides” library in RStudio.

Results: 2D diagrams revealed distinct distributions of peptides based on molecular weight and isoelectric point, dependent on enzyme specificity. In the combined hydrolysis model, 4 bitter peptides, 3 types of bitter amino acids, and 6 antioxidant peptides were identified.

Conclusion: Bioinformatic modeling enables the prediction of enzymatic changes in milk proteins during storage, their impact on quality, and enhances the efficiency of related experiments. These findings may support the development of approaches for assessing dairy product storage conditions and identifying quality markers.

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