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Studies of two different cancer cell lines activities (MDAMB-231 and SK-N-SH) of imidazo[1,2-a]pyrazine derivatives by combining DFT and QSAR results

Samir Chtita, Majdouline Larif, Mounir Ghamali, Azeddine Adad, Hmamouchi Rachid Mohammed. Bouachrine3 and Tahar Lakhlifi

To establish a quantitative structure-activity relationship for cytotoxic effects of two against different cancer cell lines, a series of thirteen imidazo[1,2-a]pyrazine 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 a neural network (NN). 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 (Formula Weight, Molar Volume, Molecular Weight, Molar Refractivity, Parachor, Density, Refractive Index, Surface Tension and Polarizability) and the electronic descriptors (total energy (E), highest occupied molecular orbital energy (EHOMO), lowest unoccupied molecular orbital energy, (ELUMO) difference between the LUMO and the HOMO energy (Gap), total dipole moment of the molecules (), absolute hardness (), absolute electron negativity () and reactivity index ()) were computed with ACD/ChemSketch and Gaussian 03W program, respectively. This study shows that the MRA, PLS, and MNLR have served also to predict activities, but when compared with the results given by the ANN, we realized that the predictions fulfilled by this latter were more effective