Quantitative structure–activity relationship studies of dibenzo[a,d]cycloalkenimine derivatives for non-competitive antagonists of N-methyl-d-aspartate based on density functional theory with electronic and topological descriptors

Abstract

To establish a quantitative structure–activity relationship for non-competitive antagonists of the N-methyl-d-aspartate receptor, 48 substituted dibenzo[a,d]cycloalkenimine derivatives were analyzed by principal components, a descendant multiple regression analyses, multiple non-linear regression and an artificial neural network. We propose non-linear and linear quantitative structure–activity models and interpret the activity of the compounds by the multivariate statistical analysis. Density functional theory with Becke's three-parameter hybrid function and Lee–Yang–Parr exchange correlation functional calculations were performed to define the structure, chemical reactivity and properties of the study compounds. The topological and the electronic descriptors were computed with ACD/ChemSketch and Gaussian 03W programs, respectively. The study shows that multiple regression and multiple non-linear regression analyses predict activity; however, predictions made with a 6-2-1 artificial neural network model were more accurate. This model gave statistically significant results and showed good stability to data variation in leave-one-out cross-validation.