Quantitative structure–activity relationship modeling of renin-inhibiting dipeptides

Abstract

Partial least squares regression method was used to analyze a peptide dataset and construct inhibitory models for renin-inhibitory natural dipeptides. The models were computed with the renin-inhibitory activity as dependent variable (Y) and the peptide structural properties as predictors (X); validation was conducted using cross-validation and permutation tests. The amino acid descriptors were based on the 3- and 5-z scales of 20 coded amino acids to produce models that explained 71.6% of Y with a 33.8% predictive ability and 75.2% of Y with a predictive power of 50.8%, respectively. In both models, low molecular size amino acids with hydrophobic side chains were preferred at the N-terminus, while amino acids with bulky side chains were preferred at the C-terminus for potency. Based on the 5-z model, four Trp (W)-containing antihypertensive dipeptides (IW, LW, VW and AW) were predicted as the most potent renin inhibitors. The peptides were synthesized and in vitro inhibition assay showed that IW and LW inhibited 70% (IC₅₀, 2.3 mM) and 37% renin activity at 3.2 mM, respectively, whereas VW and AW were inactive. There was no correlation between the observed renin-inhibitory activities and angiotensin-converting enzyme inhibitory activities of the dipeptides. We concluded that the structural similarities between isoleucine and leucine could have contributed to their distinct inhibitory activity when compared to alanine and valine. Therefore, IW may be a useful template for the development of advanced forms of highly active low molecular size antihypertensive peptides and peptidomimetics.