Exploration of potential angiotensin converting enzyme inhibitory peptides generated from enzymatic hydrolysis of goat milk proteins

- Biological activities of the goat milk proteins were assessed.
- Explored the bioactive ACE-inhibitory peptides from goat milk proteins.
- Released goat milk derived ACE-inhibitory peptides are non-toxic and bitter in taste.
- Computational approaches can be an efficient tool to reduce the number of experiments.
- Goat milk proteins can be used to release potential functional ingredients.

Goat milk is seemed to be a perfect food as similar to the human's milk in nature. Goat milk proteins are potential sources for the production of bioactive peptides with various biological activities. Bioactive peptides can be used as functional ingredients in the formulation of health-enhancing nutraceuticals, and as potent drugs with positive impact on body functions. The objective of this study was to explore the potential of goat milk derived proteins as a precursor of bioactive peptides with especially reference to angiotensin converting enzyme (ACE) inhibitory peptides. The various computational approaches (BLAST, BIOPEP, and PeptideRanker) were used to predict the potential of goat milk derived proteins for releasing bioactive ACE inhibitory peptides. Pepsin and chymotrypsin A proteases were used for in silico proteolysis and pepsin majorly released the higher number of ACE inhibitory peptides as compared with chymotrypsin A. PeptideRanker tool was used to screen the most potent theoretically release bioactive ACE inhibitory peptides. Furthermore, the sensory characteristics and toxicity profile of selected most potential ACE inhibitory peptides were also studied using BIOPEP and ToxinPred tools, respectively. Bioactive peptides or hydrolysates released from the goat milk proteins can be considered for the development of nutraceuticals and pharmaceuticals products. The result of this study also provides a theoretical basis for the development of goat milk derived proteins as a suitable source for the generation of bio-functional ingredients for prevention and treatment of hypertension. This study also demonstrates the usefulness of computational approaches.

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