A descriptor of amino acids: SVRG and its application to peptide quantitative structure-activity relationship

In this work, a descriptor, SVRG (principal component scores vector of radial distribution function descriptors and geometrical descriptors), was derived from principal component analysis (PCA) of a matrix of two structural variables of coded amino acids, including radial distribution function index (RDF) and geometrical index. SVRG scales were then applied in three panels of peptide quantitative structure-activity relationships (QSARs) which were modelled by partial least squares regression (PLS). The obtained models with the correlation coefficient (R²(cum)), cross-validation correlation coefficient (Q²(LOO)) were 0.910 and 0.863 for 48 bitter-tasting dipeptides; 0.968 and 0.931 for 21 oxytocin analogues; and 0.992 and 0.954 for 20 thromboplastin inhibitors. Satisfactory results showed that SVRG contained much chemical information relating to bioactivities. The approach may be a useful structural expression methodology for studies on peptide QSAR.