IN SILICO IDENTIFICATION OF NOVEL EGFR TYROSINE KINASE INHIBITORS ASSOCIATED WITH NON-SMALL CELL LUNG CANCER FROM PHYTOCHEMICAL LIBRARY
Keywords:
Pharmacophore., Molecular docking,, Machine learning,, Phytochemical inhibitor,, Non-small cell lung cancer,Abstract
Inhibition of EGFR by targeting its tyrosine kinase domain is a worldwide accepted treatment of non-small cell lung cancer (NSCLC). Plant derived compounds show excellent potential as cancer growth inhibitors. Present study aims to identify potent plant derived inhibitors against EGFR tyrosine kinase ATP binding domain. 50 phytochemicals from different plant sources were screened by machine learning model and molecular docking. After that admetSAR server was used to check toxicity profile of screened phytochemicals followed by pharmacophore analysis. Finally six phytochemicals were obtained as potent natural inhibitors of EGFR tyrosine kinase which could be used as drug candidate against NSCLC in future.