Literature DB >> 24491504

Ensemble docking and molecular dynamics identify knoevenagel curcumin derivatives with potent anti-EGFR activity.

Inderjit S Yadav1, Prajwal P Nandekar2, Shambhavi Srivastavaa, Shambhavi Shrivastava3, Abhay Sangamwar2, Ashok Chaudhury4, Subhash Mohan Agarwal5.   

Abstract

Epidermal growth factor receptor tyrosine kinase (EGFR-TK) is an attractive target for cancer therapy. Despite a number of effective EGFR inhibitors that are constantly expanding and different methods being employed to obtain novel compounds, the search for newer EGFR inhibitors is still a major scientific challenge. In the present study, a molecular docking and molecular dynamics investigation has been carried out with an ensemble of EGFR-TK structures against a synthetically feasible library of curcumin analogs to discover potent EGFR inhibitors. To resolve protein flexibility issue we have utilized 5 EGFR wild type crystal structures during docking as this gives improved possibility of identifying an active compound as compared to using a single crystal structure. We then identified five curcumin analogs representing different scaffolds that can serve as lead molecules. Finally, the 5 ns molecular dynamics simulation shows that knoevenagel condensate of curcumin specifically C29 and C30 can be used as starting blocks for developing effective leads capable of inhibiting EGFR.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Curcumin; EGFR; Ensemble docking; Molecular dynamics; Tyrosine kinase

Mesh:

Substances:

Year:  2014        PMID: 24491504     DOI: 10.1016/j.gene.2014.01.056

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  5 in total

1.  Computational identification of natural product inhibitors against EGFR double mutant (T790M/L858R) by integrating ADMET, machine learning, molecular docking and a dynamics approach.

Authors:  Subhash M Agarwal; Prajwal Nandekar; Ravi Saini
Journal:  RSC Adv       Date:  2022-06-07       Impact factor: 4.036

2.  Acrolein and thiol-reactive electrophiles suppress allergen-induced innate airway epithelial responses by inhibition of DUOX1 and EGFR.

Authors:  Karamatullah Danyal; Willem de Jong; Edmund O'Brien; Robert A Bauer; David E Heppner; Andrew C Little; Milena Hristova; Aida Habibovic; Albert van der Vliet
Journal:  Am J Physiol Lung Cell Mol Physiol       Date:  2016-09-09       Impact factor: 5.464

Review 3.  Molecular targets of naturopathy in cancer research: bridge to modern medicine.

Authors:  Aamir Ahmad; Kevin R Ginnebaugh; Yiwei Li; Subhash B Padhye; Fazlul H Sarkar
Journal:  Nutrients       Date:  2015-01-06       Impact factor: 5.717

4.  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

5.  EGFRisopred: a machine learning-based classification model for identifying isoform-specific inhibitors against EGFR and HER2.

Authors:  Ravi Saini; Subhash Mohan Agarwal
Journal:  Mol Divers       Date:  2021-08-03       Impact factor: 2.943

  5 in total

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