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

3D-QSAR, molecular dynamics simulations, and molecular docking studies on pyridoaminotropanes and... 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 $$(q^{2})$$ ( q 2 ) , conventional coefficient $$(r^{2})$$ ( r 2 ) , and predicted correlation coefficient $$(r^{2}_{\mathrm{pred}})$$ ( r pred 2 ) 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), $$q^{2}$$ q 2 , $$r^{2}$$ r 2 and $$r^{2}_{\mathrm{pred}}$$ r pred 2 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Molecular Diversity Springer Journals

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

, Volume 21 (3) – Jun 2, 2017
19 pages

/lp/springer_journal/3d-qsar-molecular-dynamics-simulations-and-molecular-docking-studies-Ck00m0odpV
Publisher
Springer International Publishing
Copyright © 2017 by Springer International Publishing Switzerland
Subject
Life Sciences; Biochemistry, general; Organic Chemistry; Polymer Sciences; Pharmacy
ISSN
1381-1991
eISSN
1573-501X
D.O.I.
10.1007/s11030-017-9752-9
Publisher site
See Article on Publisher Site

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

Journal

Molecular DiversitySpringer Journals

Published: Jun 2, 2017

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