Quantitative Structure Activity Relationship (QSAR) and molecular docking studies were carried out on some novel compounds to generate a good QSAR model that relate the anti-breast cancer activity values with their molecular structure. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were employed to select the descriptors that were used to build the models. The best model built was found to have statistical validation values of squared correlation coefficient R 2 = 0.9845, adjusted squared correlation coefficient = 0.9814, cross validation coefficient = 0.9763 and an external squared correlation coefficient = 0.8240 which was used to confirm the validation of the model. The docking results showed that ligands 12 with binding energy (-9.3kcalmol -1 ) have the highest binding affinity when compared to the reference drug doxorubicin with binding energy (-6.8kcalmol -1 ). The stability and robustness of the built model showed that new anti-breast cancer agents can be design from these derivatives.
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