Abstract
A database consisting of 224 di- to tetradecapeptides and five amino acids was compiled to study quantitative structure-activity relationships of bitter peptides. Partial least-squares regression-1 analysis was conducted using the amino acid three z-scores and/or three parameters (total hydrophobicity, residue number, and log mass values) as X-variables and bitterness values (log 1/T where T is the bitterness threshold) as Y-variables. Using the three parameters only, significant models (p < 0.001) were obtained describing the entire data set as well as data subsets, except that comprised only of octa- to tetradecapeptides. For data sets comprising different peptide lengths, the models were improved by including the three z-scores at the N-terminal and C-terminal positions. Correlation coefficients for bitterness prediction of 48 dipeptides and 12 pentapeptides were 0.75 (RMSEP = 0.53) and 0.90 (RMSEP = 0.48), respectively. Bulky hydrophobic amino acids at the C terminus and bulky basic amino acids at the N terminus were highly correlated to bitterness.
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