Identification of potent EGFR-TKD inhibitors from NPACT database through combined computational approaches

Abstract

Cancer is the world’s second leading cause of death, and there are no approved herbal therapies. The epidermal growth factor receptor tyrosine kinase (EGFR-TK) receptor is a transmembrane protein with eight domains that is found in almost every cancer type and plays an important role in abnormal cell cellular function and causes malignant outcomes. The current study aimed to virtually screen phytochemicals from the NPACT database against EGFR-TKD and also to identify potential inhibitors of this transmembrane protein among plant candidates for anticancer drug development. The docking scores of the chosen phytochemicals were compared with the control (erlotinib). Kurarinone, (2S)-2-methoxykurarnione, and Sophoraflavanone-G exhibited a stronger binding affinity of −18.102 kcal/mol, −14.243 kcal/mol, and −13.759 kcal/mol than erlotinib −12.783 kcal/mol. Moreover, several online search engines were used to predict ADME and toxicity. The drug-likeness of selected phytochemicals was higher than the reference (erlotinib). A 100 ns molecular dynamic (MD) simulation was also applied to the docked conformations to examine the stability and molecular mechanics of protein-ligand interactions. Furthermore, the calculated molecular mechanics Poisson Boltzmann surface area energy of (2S)-2-methoxykurarnione was found to be −129.555 ± 0.512 kJ/mol, which approximately corresponds to the free energy of the reference molecule −130.595 ± 0.908 kJ/mol. We identify phytoconstituents present in Sophora flavescens from the NPACT database, providing key insights into tyrosine kinase inhibition and may serve as better chemotherapeutic agents. Experimental validation is required to determine the anti-EGFR potency of the potent lead molecules discussed in this study.

Communicated by Ramaswamy H. Sarma

Keywords:

• Phytochemicals
• ADMET
• molecular docking
• molecular dynamics simulations
• MM-PBSA

Acknowledgment

Showkat Ahmad Mir wishes to acknowledge DBT-Builder Interdisciplinary Life Sciences Research for providing a fellowship. Showkat Ahmad Mir wishes to acknowledge Dr. Ibrahim Khalifa, assistant professor at Food Tech., Benha University, Egypt, for providing access to MOE09 tools.

Authors’ contributions

All authors contribute equally

Disclosure statement

Authors declare no financial competing interact.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.