Literature DB >> 21400356

Pharmacophore modelling, molecular docking and virtual screening for EGFR (HER 1) tyrosine kinase inhibitors.

A K Gupta1, S S Bhunia, V M Balaramnavar, A K Saxena.   

Abstract

A pharmacophore model has been developed using diverse classes of epidermal growth factor receptor (EGFR) tyrosine kinase (TK) inhibitors useful in the treatment of human tumours. Among the top 10 generated hypotheses, the second hypothesis, with one hydrogen bond acceptor, one ring aromatic and three hydrophobic features, was found to be the best on the basis of Cat Scramble validation as well as test set prediction (r(training) = 0.89, r(test) = 0.82). The model also maps well to the external test set molecules as well as clinically active molecules and corroborates the docking studies. Finally, 10 hits were identified as potential leads after virtual screening of ZINC database for EGFR TK inhibition. The study may facilitate the designing and discovery of novel EGFR TK inhibitors.

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Year:  2011        PMID: 21400356     DOI: 10.1080/1062936X.2010.548830

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  8 in total

1.  Identification of novel potential HIF-prolyl hydroxylase inhibitors by in silico screening.

Authors:  Mahesh Kumar Teli; G K Rajanikant
Journal:  Mol Divers       Date:  2011-11-01       Impact factor: 2.943

2.  In silico screening for identification of pyrrolidine derivatives dipeptidyl peptidase-IV inhibitors using COMFA, CoMSIA, HQSAR and docking studies.

Authors:  M C Sharma; S Jain; R Sharma
Journal:  In Silico Pharmacol       Date:  2017-10-23

3.  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

4.  Multiple target drug cocktail design for attacking the core network markers of four cancers using ligand-based and structure-based virtual screening methods.

Authors:  Yung-Hao Wong; Chih-Lung Lin; Ting-Shou Chen; Chien-An Chen; Pei-Shin Jiang; Yi-Hua Lai; Lichieh Chu; Cheng-Wei Li; Jeremy J W Chen; Bor-Sen Chen
Journal:  BMC Med Genomics       Date:  2015-12-09       Impact factor: 3.063

5.  Modelling inhibition of avian aromatase by azole pesticides.

Authors:  A K Saxena; J Devillers; S S Bhunia; E Bro
Journal:  SAR QSAR Environ Res       Date:  2015       Impact factor: 3.000

6.  Osimertinib or EGFR-TKIs/chemotherapy in patients with EGFR-mutated advanced nonsmall cell lung cancer: A meta-analysis.

Authors:  Lei Huang; Hao Huang; Xiao-Ping Zhou; Jin-Feng Liu; Chun-Rong Li; Min Fang; Jun-Rong Wu
Journal:  Medicine (Baltimore)       Date:  2019-10       Impact factor: 1.817

7.  Ligand-Based Pharmacophore Modeling, Molecular Docking, and Molecular Dynamic Studies of Dual Tyrosine Kinase Inhibitor of EGFR and VEGFR2.

Authors:  Frangky Sangande; Elin Julianti; Daryono Hadi Tjahjono
Journal:  Int J Mol Sci       Date:  2020-10-21       Impact factor: 5.923

8.  Identification of 3-((1-(Benzyl(2-hydroxy-2-phenylethyl)amino)-1-oxo-3-phenylpropan-2-yl)carbamoyl)pyrazine-2-carboxylic Acid as a Potential Inhibitor of Non-Nucleosidase Reverse Transcriptase Inhibitors through InSilico Ligand- and Structure-Based Approaches.

Authors:  Deepti Mathpal; Tahani M Almeleebia; Kholoud M Alshahrani; Mohammad Y Alshahrani; Irfan Ahmad; Mohammed Asiri; Mehnaz Kamal; Talha Jawaid; Swayam Prakash Srivastava; Mohd Saeed; Vishal M Balaramnavar
Journal:  Molecules       Date:  2021-08-30       Impact factor: 4.411

  8 in total

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