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2000
Volume 10, Issue 1
  • ISSN: 2212-697X
  • E-ISSN: 2212-6988

Abstract

Background

Newer chemical entities are created and synthesis has been made feasible by a variety of computer-aided drug design (CAAD) techniques. In addition to facilitating the visualisation of the ligand-target binding process, the application of methodologies and structure-based drug design (SBDD) allows for the prediction of receptor affinities and significant binding pocket locations.

Objective

The goal of the current study was to identify new quinoline derivatives by computational methods specially designed to bind the EGFR receptor in the treatment of breast cancer.

Materials and Methods

ChemAxon Marvin Sketch 5.11.5 was used to create derivatives of quinolines. The admetSAR online web tools and SwissADME were utilised to forecast the toxicity and pharmacokinetic characteristics of several substances. A multitude of software programmes, such as Autodock 1.1.2, MGL Tools 1.5.6, Procheck, Protparam ExPasy tool, PyMOL, and Biovia Discovery Studio Visualizer v20.1.0.19295 were also employed to ascertain the ligand-receptor interactions between quinoline derivatives and the target receptor (PDB -5GNK).

Results

Almost all components were shown to be less hazardous, orally consumable and to have the appropriate pharmacokinetic characteristics based on study. All newly generated derivative compounds have higher docking scores when compared to the widely used medication sorafenib.

Conclusion

Interactions with quinoline analogues boost binding energy and the number of H-bonds produced, making them a suitable place to start when creating compounds for further exploration. The quinoline moiety increases its potential as a novel therapy alternative for breast cancer and could facilitate more comprehensive , , chemical-based, and pharma studies by medicinal chemists.

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Investigation of Novel Quinoline Derivatives Targeting Epidermal Growth Factor Receptors as Anticancer Agents a Computational Approach
Clinical Cancer Drugs 10, E2212697X335334 (2024); https://doi.org/10.2174/012212697X335334241101023647
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  • Article Type:     Research Article
Keyword(s): binding affinity; bioavailability score; C-met; CADD; EGFR; molecular docking; pharmacokinetics

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