Abstract: Quantitative structure-activity relationships (QSARs) are essential to optimize the structure to give desired biological activities in drug development. In this paper, a new descriptor, principal component scores vector of structural and topological variables (VSTV), was derived from a principal components analysis of a matrix of 25 structural and topological variables of 20 natural amino acids. Using the method of partial least squares regression, the scales were then applied in QSARs of 58 angiotensin-converting enzyme inhibitors, 12 bactericidal peptides and 20 thromboplastin inhibitors. Good results were obtained and the multiple correlation coefficients (R2) and cross-validated R2 (Q2) of three models were 0.789, 0.767; 0.996, 0.879; 0.981, 0.480, respectively.

Key words: Amino acids, Peptide, Topology, Principal component scores vector of structural and topological variables (VSTV), Quantitative structure activity relationship, Partial least squares regression