Drug Design for ALK-Positive NSCLC: an Integrated Pharmacophore-Based 3D QSAR and Virtual Screening Strategy

Abstract

The increasing death rates related to anaplastic lymphoma kinase (ALK)-positive lung cancer culminated in a significant interest in the discovery of novel inhibitors for ALK. In the present research work, pharmacophore-based 3D QSAR modeling and virtual screening strategy have been carried out to address these issues. Initially, a five-point pharmacophore model was developed using the biological data of 50 compounds which includes an FDA-approved ALK inhibitor, crizotinib. Using the generated pharmacophore, a 3D QSAR model was developed and used as a query to screen the DrugBank database. The model was found to be significant (R ² = 0.9696) with an excellent predictive accuracy (Q ² = 0.7652) as confirmed through validation of the both training and test molecule activities. Further, Glide docking score and absorption, distribution, metabolism and excretion properties were used to filter the screened candidates. Overall, our analysis results in three hits namely TR1, FAL, ZYW with higher docking scores, and good pharmaceutically relevant properties with increased CNS involvement. It is worth mentioning that FAL and ZYW were found to possess scaffolds with specific activity against ALK protein. We presume that the results obtained from this computational study are of immense importance in the rational designing of novel and more potent ALK inhibitors.