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3D-QSAR, molecular dynamics simulations, and molecular docking studies on pyridoaminotropanes and tetrahydroquinazoline as mTOR inhibitors

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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 \((q^{2})\), conventional coefficient \((r^{2})\), and predicted correlation coefficient \((r^{2}_{\mathrm{pred}})\) 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), \(q^{2}\), \(r^{2}\) and \(r^{2}_{\mathrm{pred}}\) 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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Acknowledgements

The authors are thankful to Nirma University, Ahmedabad, India for providing necessary facilities to carry out the research work, which is a part of Doctor of Philosophy (Ph.D.) research work of Udit Chaube, to be submitted to Nirma University, Ahmedabad, India. Udit Chaube is thankful to Department of Science and Technology (DST), Govt. of India for providing INSPIRE fellowship (IF140932).

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  1. Department of Pharmaceutical Chemistry, Institute of Pharmacy, Nirma University, S. G. Highway, Chharodi, Ahmedabad, 382 481, India

    Udit Chaube & Hardik Bhatt

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  1. Udit Chaube
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Correspondence to Hardik Bhatt.

Electronic supplementary material

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11030_2017_9752_MOESM1_ESM.pdf

Supplementary Materials: Scatter plot of CoMFA model, CoMSIA model (SEHDA), and CoMSIA model (SEH); molecular dynamics simulations study of compounds 19, 15 and 42 with respect to potential energy, kinetic energy and temperature; Plot of RMSD values of docked ligand Vs MD simulation time; molecular docking study of compounds 19, 15 and 42; designed molecules with tetrahydroquinoline scaffold; general features required for mTOR inhibition in compound S(1) and its simulated docked conformer in mTOR are provided in the supplementary material. (pdf 3.37MB)

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Chaube, U., Bhatt, H. 3D-QSAR, molecular dynamics simulations, and molecular docking studies on pyridoaminotropanes and tetrahydroquinazoline as mTOR inhibitors. Mol Divers 21, 741–759 (2017). https://doi.org/10.1007/s11030-017-9752-9

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