Abstract
A new descriptor, vector of principal component scores for GETAWAY index, was derived from a principal components analysis of a matrix of 197 GETAWAY indexes of 20 natural amino acids. The scale was then applied to construct three panels of polypeptide quantitative structure activity relationship (QSAR) based on partial least squares (PLS) regression. The correlation coefficient (R2 cum) and cross-validation correlation coefficient (Q2 cum) of the obtained models were 0.887 and 0.753 for 48 bitter tasting dipeptides, 0.995 and 0.708 for 31 bradykinin-potentiating pentapeptides, 0.999 and 0.802 for 20 thromboplastin inhibitors, respectively. The satisfactory results showed that, as new amino acid scales, data of VSGETAWAY may be a useful structural expression methodology for study on peptide QSAR due to its many advantages such as easy manipulation, plentiful structural information and high characterization competence.
Published Version
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