Abstract

Cancer is a second major disease after metabolic disorders where the number of cases of death is increasing gradually. Mammalian target of rapamycin (mTOR) is one of the most important targets for treatment of cancer, specifically for breast and lung cancer. In the present research work, Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) studies were performed on 50 compounds reported as mTOR inhibitors. Three different alignment methods were used, and among them, distill method was found to be the best method. In CoMFA, leave-one-out cross-validated coefficients [Formula: see text], conventional coefficient [Formula: see text], and predicted correlation coefficient [Formula: see text] values were found to be 0.664, 0.992, and 0.652, respectively. CoMSIA study was performed in 25 different combinations of features, such as steric, electrostatic, hydrogen bond donor, hydrogen bond acceptor, and hydrophobic. From this, a combination of steric, electrostatic, hydrophobic (SEH), and a combination of steric, electrostatic, hydrophobic, donor, and acceptor (SEHDA) were found as best combinations. In CoMSIA (SEHDA), [Formula: see text], [Formula: see text] and [Formula: see text] were found to be 0.646, 0.977, and 0.682, respectively, while in the case of CoMSIA (SEH), the values were 0.739, 0.976, and 0.779, respectively. Contour maps were generated and validated by molecular dynamics simulation-assisted molecular docking study. Highest active compound 19, moderate active compound 15, and lowest active compound 42 were docked on mTOR protein to validate the results of our molecular docking study. The result of the molecular docking study of highest active compound 19 is in line with the outcomes generated by contour maps. Based on the features obtained through this study, six novel mTOR inhibitors were designed and docked. This study could be useful for designing novel molecules with increased anticancer activity.

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