To establish a quantitative structure-activity relationship for antibacterial activity against Staphylococcus aureus and Bacillus subtilis, a series of seventeen 1,3-disubstituted-1H-naphtho[1,2-e][1,3]oxazine derivatives molecules was submitted to a principal components analysis (PCA), to a multiple regression analysis (MRA), to a regression partial least squares (PLS), to a non-linear regression (RNLM) and to an artificial neural network (ANN). We accordingly propose a quantitative model, and we interpret the activity of the compounds relying on the multivariate statistical analysis. Density functional theory (DFT) and ab-initio molecular orbital calculations have been carried out in order to get insights into the structure, chemical reactivity and property information for the series of study compounds. The topological descriptors were computed with ACD/ChemSketch and Gaussian 03W program, respectively. This study shows that the MRA, PLS, and ANN have served also to predict activities, but when compared with the results given by the RNLM, we realized that the predictions fulfilled by this latter were more effective.
