Literature DB >> 28577112

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

Udit Chaube1, Hardik Bhatt2.   

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.

Entities:  

Keywords:  Comparative Molecular Field Analysis (CoMFA); Comparative Molecular Similarity Indices Analysis (CoMSIA); Molecular docking; Molecular dynamics simulations; Three-dimensional quantitative structure activity relationship (3D-QSAR); mTOR

Mesh:

Substances:

Year:  2017        PMID: 28577112     DOI: 10.1007/s11030-017-9752-9

Source DB:  PubMed          Journal:  Mol Divers        ISSN: 1381-1991            Impact factor:   2.943


  21 in total

1.  QSAR models of cytochrome P450 enzyme 1A2 inhibitors using CoMFA, CoMSIA and HQSAR.

Authors:  J Sridhar; M Foroozesh; C L Klein Stevens
Journal:  SAR QSAR Environ Res       Date:  2011-10-17       Impact factor: 3.000

2.  Structural investigations of anthranilimide derivatives by CoMFA and CoMSIA 3D-QSAR studies reveal novel insight into their structures toward glycogen phosphorylase inhibition.

Authors:  U Saqib; B Kumar; M I Siddiqi
Journal:  SAR QSAR Environ Res       Date:  2011-05-27       Impact factor: 3.000

3.  Structure based 3D-QSAR studies of Interleukin-2 inhibitors: Comparing the quality and predictivity of 3D-QSAR models obtained from different alignment methods and charge calculations.

Authors:  Sobia Ahsan Halim
Journal:  Chem Biol Interact       Date:  2015-06-04       Impact factor: 5.192

Review 4.  Targeting PI3K/AKT/mTOR pathway in non small cell lung cancer.

Authors:  Claudia Fumarola; Mara A Bonelli; Pier Giorgio Petronini; Roberta R Alfieri
Journal:  Biochem Pharmacol       Date:  2014-05-24       Impact factor: 5.858

5.  3D-QSAR (CoMFA and CoMSIA) and pharmacophore (GALAHAD) studies on the differential inhibition of aldose reductase by flavonoid compounds.

Authors:  Julio Caballero
Journal:  J Mol Graph Model       Date:  2010-09-21       Impact factor: 2.518

6.  Discovery and Biological Profiling of Potent and Selective mTOR Inhibitor GDC-0349.

Authors:  Zhonghua Pei; Elizabeth Blackwood; Lichuan Liu; Shiva Malek; Marcia Belvin; Michael F T Koehler; Daniel F Ortwine; Huifen Chen; Frederick Cohen; Jane R Kenny; Philippe Bergeron; Kevin Lau; Cuong Ly; Xianrui Zhao; Anthony A Estrada; Tom Truong; Jennifer A Epler; Jim Nonomiya; Lan Trinh; Steve Sideris; John Lesnick; Linda Bao; Ulka Vijapurkar; Sophie Mukadam; Suzanne Tay; Gauri Deshmukh; Yung-Hsiang Chen; Xiao Ding; Lori S Friedman; Joseph P Lyssikatos
Journal:  ACS Med Chem Lett       Date:  2012-11-29       Impact factor: 4.345

7.  5,3'-Dihydroxy-6,7,4'-trimethoxyflavanone exerts its anticancer and antiangiogenesis effects through regulation of the Akt/mTOR signaling pathway in human lung cancer cells.

Authors:  Ki Mo Kim; Deok Rim Heo; Jun Lee; Jong-Shik Park; Myung-Gi Baek; Jin-Mu Yi; Haejin Kim; Ok-Sun Bang
Journal:  Chem Biol Interact       Date:  2014-11-18       Impact factor: 5.192

Review 8.  Current treatment strategies for inhibiting mTOR in cancer.

Authors:  Francesca Chiarini; Camilla Evangelisti; James A McCubrey; Alberto M Martelli
Journal:  Trends Pharmacol Sci       Date:  2014-12-11       Impact factor: 14.819

9.  mTOR and cancer: many loops in one pathway.

Authors:  Alejo Efeyan; David M Sabatini
Journal:  Curr Opin Cell Biol       Date:  2009-11-27       Impact factor: 8.382

10.  3D-QSAR (CoMFA, CoMFA-RG, CoMSIA) and molecular docking study of thienopyrimidine and thienopyridine derivatives to explore structural requirements for aurora-B kinase inhibition.

Authors:  Ankit Borisa; Hardik Bhatt
Journal:  Eur J Pharm Sci       Date:  2015-09-04       Impact factor: 4.384

View more
  1 in total

1.  Molecular Modeling and Design Studies of Purine Derivatives as Novel CDK2 Inhibitors.

Authors:  Gaomin Zhang; Yujie Ren
Journal:  Molecules       Date:  2018-11-09       Impact factor: 4.411

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.