QSAR and Structure-Based Docking Studies of Aryl Pyrido[2,3-d]pyrimidin-7(8H)-ones: An Attempt to Anticancer Drug Design

The target of the present study has been to carry out computer-aided anticancer drug design utilizing genetic algorithm-multiple linear regression (GA-MLR) based quantitative structure activity relationship (QSAR) of fibroblast growth factor (FGFr) inhibition of pyrido[2,3-d]pyrimidine-7(8H)-one compounds utilizing different classes of computed structural descriptors. A QSAR model was developed utilizing a combination of constitutional, functional group, geometrical and atom-centered fragment indices by multiple linear regression method and the model validation was performed by searching the predictability of the QSAR models. After outlier analyses through applicability domain, the model validation results were improved. In this connection, molecular docking studies were performed to predict the mode of binding and important structural features necessary for producing biological activities. This attempt could be helpful for further modeling of potent less toxic anticancer chemotherapeutics in these congeners.