Lung cancer is the second most prevalent carcinoma around the world, and about 80% of patients are of non-small cell lung cancer (NS-CLC). Epidermal growth factor receptor (EGFR) is the most expressed protein kinases in lung cancer and hence can be used in target-related anti-cancer therapy. Here, computational approach is used for the exploration of the anti-cancer potential of new steroid derivatives as previously no in vitro data was available for them. Initially, DFT calculations of all compounds were determined to analyze the electronic density of optimized structures. The HOMO and LUMO orbital analysis of all derivatives was analyzed, to investigate the reactivity of compounds. Afterwards, optimized structures were used for molecular docking studies in which all ouabagenin derivatives were docked within the EGFR active site using MOE software. Moreover, anti-cancer potential of selected derivatives was evaluated on the basis of binding interactions with three anti-cancer proteins. The binding scores of these compounds were compared with the FDA-approved drug, i.e., gefitinib. The findings of current study suggested that selected derivatives exhibited significant inhibiting potential of anti-cancer proteins and EGFR. Particularly, compound OD3 is the potent inhibitor of anti-cancer and EGFR protein with the highest binding energies. These novel steroidal derivatives are subjected to in silico analysis for the first time against lung cancer. These compounds possess potential anti-cancerous properties and can be explored further for in vitro and in vivo studies.
Keywords: DFTs; EGFR; Lung cancer; Molecular docking; Ouabagenin derivatives; Steroids.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.