AMINO-ACIDS CHARACTERIZATION BY GRID AND MULTIVARIATE DATA-ANALYSIS

The twenty coded amino acids have been characterized by their interaction energies, calculated by the program GRID, with six different probes mimicking various functional groups which can be involved in peptide-peptide interactions. Principal Component Analysis (PCA) have been used to derive amino acids principal properties and comparing the amino acids classification obtained with the one derived by the previous published amino acids z-scales. Partial Least Squares (PLS) method has been used to test the performance of GRID probe interaction energies and the newly derived principal properties in peptide's QSAR modeling. A better separation of amino acids according to the electronic features of the side chain is obtained. The inhibitory activity of the set of peptides considered has been satisfactorally modelled.