A Novel MHDV Descriptor for Dipeptide QSAR Studies

A novel molecular holographic distance vector (MHDV) is proposed to characterize the structures of the peptide molecules and employed to relate to the biological activities of the peptides by means of principal component regression (PCR) method. For two pan els of dipeptides, the correlation coefficient (R) between the estimated and the observed activities are respectively 0.9370 and 0.9585 and the R obtained by cross-validation method are respectively 0.8676 and 0.9295, which is the best result to date for the two sets of dipeptides. The novel MHDV descriptor only depends on distance matrix and various atomic types of non-hydrogen atoms in a molecule and requires no 3D structural information, so, it is a very simple and easy to use descriptor.