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Keywords:

  • angiotensin converting enzyme;
  • bioactive peptides;
  • QSAR;
  • partial least squares regression

Abstract

Models for angiotensin converting enzyme (ACE) inhibitory peptides with varied lengths are proposed based on results from partial least square regression analysis of the potency of known peptides. Modeling was performed using partial least square regression with inhibitory activity of peptides as the dependent variable (Y) and the physicochemical properties of amino acids as the predictor X matrix. Variable importance in the projection (VIP) analysis of individual amino acid residues at each position revealed that the C-terminal tetrapeptide residues of long-chain peptides were more important to their ACE-inhibitory activity than the C-terminal tripeptide residues. The most likely preferred amino acid residues starting from C-terminus are tyrosine and cysteine for the first position, histidine, tryptophan and methionine for the second position with isoleucine, leucine, valine and methionine for the third position, and tryptophan for the fourth position. We concluded that the reported structural requirements of ACE-inhibitory peptides provide useful information that can be used for the development of more efficacious ACE-inhibitory peptides.