Literature DB >> 19590909

In silico QSAR studies of anilinoquinolines as EGFR inhibitors.

Farhan Ahmad Pasha1, Muhammad Muddassar, Anil Kumar Srivastava, Seung Joo Cho.   

Abstract

Members of the epidermal growth factor receptor (EGFR) family of proteins are frequently overactive in solid tumors. A relatively new therapeutic approach to inhibit the kinase activity is the use of ATP-competitive small molecules. In silico techniques were employed to identify the key interactions between inhibitors and their protein receptors. A series of EGFR inhibitory anilinoquinolines was studied within the framework of hologram quantitative structure activity relationship (HQSAR), density functional theory (DFT)-based QSAR, and three-dimensional (3D) QSAR (CoMFA/CoMSIA). The HQSAR analysis implied that substitutions at certain sites on the inhibitors play an important role in EGFR inhibition. DFT-based QSAR results suggested that steric and electronic interactions contributed significantly to the activity. Ligand-based 3D-QSAR and receptor-guided 3D-QSAR analyses such as CoMFA and CoMSIA techniques were carried out, and the results corroborated the previous two approaches. The 3D QSAR models indicated that steric and hydrophobic interactions are dominant, and that substitution patterns are an important factor in determining activity. Molecular docking was helpful in identifying a bioactive conformer as well as a plausible binding mode. The docked geometry-based CoMFA model with steric and electrostatic fields effect gave q(2) = 0.66, r(2) = 0.94 with r(2) (predictive) = 0.72. Similarly, CoMSIA with hydrophobic field gave q(2) = 0.59, r(2) = 0.85 with r(2) (predictive) = 0.63. Bulky groups around site 3 of ring "C", and hydrophilic and bulky groups at position 6 of ring "A" are desirable, with a hydrophobic and electron-donating group at site 7 of ring "A" being helpful. Accordingly, potential EGFR inhibitors may be designed by modification of known inhibitors.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19590909     DOI: 10.1007/s00894-009-0534-x

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  19 in total

Review 1.  Comparative QSAR study of tyrosine kinase inhibitors.

Authors:  A Kurup; R Garg; C Hansch
Journal:  Chem Rev       Date:  2001-08       Impact factor: 60.622

2.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.

Authors:  R D Cramer; D E Patterson; J D Bunce
Journal:  J Am Chem Soc       Date:  1988-08-01       Impact factor: 15.419

3.  Binding mode of the 4-anilinoquinazoline class of protein kinase inhibitor: X-ray crystallographic studies of 4-anilinoquinazolines bound to cyclin-dependent kinase 2 and p38 kinase.

Authors:  L Shewchuk; A Hassell; B Wisely; W Rocque; W Holmes; J Veal; L F Kuyper
Journal:  J Med Chem       Date:  2000-01-13       Impact factor: 7.446

Review 4.  Prevalence of aberrant expression of the epidermal growth factor receptor in human cancers.

Authors:  W J Gullick
Journal:  Br Med Bull       Date:  1991-01       Impact factor: 4.291

5.  Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity.

Authors:  G Klebe; U Abraham; T Mietzner
Journal:  J Med Chem       Date:  1994-11-25       Impact factor: 7.446

Review 6.  Targeting EGFR and HER-2 receptor tyrosine kinases for cancer drug discovery and development.

Authors:  Shantaram Kamath; John K Buolamwini
Journal:  Med Res Rev       Date:  2006-09       Impact factor: 12.944

7.  Tyrosine kinase inhibitors. 5. Synthesis and structure-activity relationships for 4-[(phenylmethyl)amino]- and 4-(phenylamino)quinazolines as potent adenosine 5'-triphosphate binding site inhibitors of the tyrosine kinase domain of the epidermal growth factor receptor.

Authors:  G W Rewcastle; W A Denny; A J Bridges; H Zhou; D R Cody; A McMichael; D W Fry
Journal:  J Med Chem       Date:  1995-09-01       Impact factor: 7.446

8.  Tyrosine kinase inhibitors. 9. Synthesis and evaluation of fused tricyclic quinazoline analogues as ATP site inhibitors of the tyrosine kinase activity of the epidermal growth factor receptor.

Authors:  G W Rewcastle; B D Palmer; A J Bridges; H D Showalter; L Sun; J Nelson; A McMichael; A J Kraker; D W Fry; W A Denny
Journal:  J Med Chem       Date:  1996-02-16       Impact factor: 7.446

9.  Structure of the epidermal growth factor receptor kinase domain alone and in complex with a 4-anilinoquinazoline inhibitor.

Authors:  Jennifer Stamos; Mark X Sliwkowski; Charles Eigenbrot
Journal:  J Biol Chem       Date:  2002-08-23       Impact factor: 5.157

10.  Receptor guided 3D-QSAR: a useful approach for designing of IGF-1R inhibitors.

Authors:  M Muddassar; F A Pasha; H W Chung; K H Yoo; C H Oh; S J Cho
Journal:  J Biomed Biotechnol       Date:  2008
View more
  9 in total

1.  3D-QSAR studies and molecular docking on [5-(4-amino-1H-benzoimidazol-2-yl)-furan-2-yl]-phosphonic acid derivatives as fructose-1,6-biphophatase inhibitors.

Authors:  Ping Lan; Mei-Qi Xie; Yue-Mei Yao; Wan-Na Chen; Wei-Min Chen
Journal:  J Comput Aided Mol Des       Date:  2010-10-20       Impact factor: 3.686

2.  Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors.

Authors:  Xian-qiang Sun; Lei Chen; Yao-zong Li; Wei-hua Li; Gui-xia Liu; Yao-quan Tu; Yun Tang
Journal:  Acta Pharmacol Sin       Date:  2013-12-16       Impact factor: 6.150

3.  Identification of potent EGFR inhibitors from TCM Database@Taiwan.

Authors:  Shun-Chieh Yang; Su-Sen Chang; Hsin-Yi Chen; Calvin Yu-Chian Chen
Journal:  PLoS Comput Biol       Date:  2011-10-13       Impact factor: 4.475

4.  Prediction of inhibitory activity of epidermal growth factor receptor inhibitors using grid search-projection pursuit regression method.

Authors:  Hongying Du; Zhide Hu; Andrea Bazzoli; Yang Zhang
Journal:  PLoS One       Date:  2011-07-21       Impact factor: 3.240

5.  QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest.

Authors:  Harinder Singh; Sandeep Singh; Deepak Singla; Subhash M Agarwal; Gajendra P S Raghava
Journal:  Biol Direct       Date:  2015-03-25       Impact factor: 4.540

6.  AutoGPA: An Automated 3D-QSAR Method Based on Pharmacophore Alignment and Grid Potential Analysis.

Authors:  Naoyuki Asakawa; Seiichi Kobayashi; Junichi Goto; Noriaki Hirayama
Journal:  Int J Med Chem       Date:  2012-11-26

7.  Investigations of Structural Requirements for BRD4 Inhibitors through Ligand- and Structure-Based 3D QSAR Approaches.

Authors:  Adeena Tahir; Rima D Alharthy; Saadia Naseem; Natasha Mahmood; Mahmood Ahmed; Khuram Shahzad; Malik Nadeem Akhtar; Abdul Hameed; Irfan Sadiq; Haq Nawaz; Muhammad Muddassar
Journal:  Molecules       Date:  2018-06-25       Impact factor: 4.411

8.  Quinazoline analogues as cytotoxic agents; QSAR, docking, and in silico studies.

Authors:  Leila Emami; Razieh Sabet; Soghra Khabnadideh; Zeinab Faghih; Parvin Thayori
Journal:  Res Pharm Sci       Date:  2021-08-19

9.  QSAR-based models for designing quinazoline/imidazothiazoles/pyrazolopyrimidines based inhibitors against wild and mutant EGFR.

Authors:  Jagat Singh Chauhan; Sandeep Kumar Dhanda; Deepak Singla; Subhash M Agarwal; Gajendra P S Raghava
Journal:  PLoS One       Date:  2014-07-03       Impact factor: 3.240

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.