The clinical outcomes in patients with non-small cell lung cancer have improved, as a result of anaplastic lymphoma kinase (ALK) inhibition. Therefore in the current study, substantial effort has been made to identify ALK inhibitors through systematic virtual screening experiment consisting of e-pharmacophore and pharmacophore perception techniques. Initially, a pharmacophore model (AAAHP.193) and an e-pharmacophore model (DDRRR) encompassing the whole dataset of 12 known ALK inhibitors were developed. The hypotheses could retrieve effective compounds from DrugBank database (8621 molecules), which were then subjected to molecular docking and ADME prediction. These approaches resulted in the identification of five hits, namely, nebivolol, HDY, D42, 796, and LZE having higher Glide docking scores and promising ADME properties with augmented CNS involvement. Moreover, molecular dynamics simulations were performed to validate the inhibitory activity of the hit compounds, and density functional theory calculations were carried out to scrutinize the chemical reactivity of the hits. Subsequent interaction and scaffold analysis identified prominent interactions of the hits with ALK kinase domain and scaffolds with anti-tumor activity against lung cancer cell lines. We strongly believe that the study provides an outlook for the sighting of novel and potent ALK inhibitors in the near future.