In-silico design, pharmacophore-based screening, and molecular docking studies reveal that benzimidazole-1,2,3-triazole hybrids as novel EGFR inhibitors targeting lung cancer

AbstractLung cancer is a complex and heterogeneous disease, which has been associated with various molecular alterations, including the overexpression and mutations of the epidermal growth factor receptor (EGFR). In this study, designed a library of 1843 benzimidazole-1,2,3-triazole hybrids and carried out pharmacophore-based screening to identify potential EGFR inhibitors. The 164 compounds were further evaluated using molecular docking and molecular dynamics simulations to understand the binding interactions between the compounds and the receptor. In-si-lico ADME and toxicity studies were also conducted to assess the drug-likeness and safety of the identified compounds. The results of this study indicate that benzimidazole-1,2,3-triazole hybrids BENZI-0660, BENZI-0125, BENZI-0279, BENZI-0415, BENZI-0437, and BENZI-1110 exhibit dock scores of −9.7, −9.6, −9.6, −9.6, −9.6, −9.6 while referencing molecule −7.9 kcal/mol for EGFR (PDB ID: 4HJO), respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of EGFR, indicating their potential as inhibitors. The in-silico ADME and toxicity studies showed that the compounds had favorable drug-likeness properties and low toxicity, further supporting their potential as therapeutic agents. Finally, performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of benzimidazole-1,2,3-triazole hybrids as promising EGFR inhibitors for the treatment of lung cancer. This research opens up a new avenue for the discovery and development of potent and selective EGFR inhibitors for the treatment of lung cancer.Communicated by Ramaswamy H. SarmaKeywords: EGFRlung cancerbenzimidazole-1,2,3-triazole hybridspharmacophore modelingADME Authors' contributionsSunil Kumar: Investigation, writing-original draft, methodology, designed and conceived the study. Iqra Ali: MD simulations and MM-GBSA analysis. Faheem Abbas: Density-functional theory analysis. Anurag Rana: Data analysis. Manoj Garg: review & editing. Sadanand Pandey: Conceptualization. Deepak Kumar: Supervision, methodology, and project administration. All authors have read and agreed to the published version of the manuscript.Disclosure statementThe authors have no conflicts of interest to declare.Additional informationFundingThe authors express their gratitude to the Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Shoolini University, Solan, Himachal Pradesh-173229, India, for the support.