Atom- and Bond-Based 2D TOMOCOMD-CARDD Approach and Ligand-Based Virtual Screening for the Drug Discovery of New Tyrosinase Inhibitors

Two-dimensional atom- and bond-based TOMOCOMD-CARDD descriptors and linear discriminant analysis (LDA) are used in this report to perform a quantitative structure-activity relationship (QSAR) study of tyrosinase-inhibitory activity. A database of inhibitors of the enzyme is collected for this study, within 246 highly dissimilar molecules presenting antityrosinase activity. In total, 7 discriminant functions are obtained by using the whole set of atom- and bond-based 2D indices. All the LDA-based QSAR models show accuracies above 90% in the training set and values of the Matthews correlation coefficient (C) varying from 0.85 to 0.90. The external validation set shows globally good classifications between 89% and 91% and C values ranging from 0.75 to 0.81. Finally, QSAR models are used in the selection/identification of the 20 new dicoumarins subset to search for tyrosinase inhibitory activity. Theoretical and experimental results show good correspondence between one anothe...