Design of novel anaplastic lymphoma kinase (ALK) inhibitors based on predictive 3D QSAR models using different alignment strategies

Abstract

Anaplastic lymphoma kinase (ALK) is involved in many signaling mechanisms that lead to cell-cycle progression; overexpression of ALK has been found in many types of cancers. ALK is a recognized target for the development of small-molecule inhibitors for the treatment of cancer. In this study, a diverse set of 71 ALK inhibitors were aligned by three different methods (pharmacophore, docking-based, and rigid body (Distill) alignment) for the development of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. The best 3D QSAR models were obtained, which used rigid body (Distill) alignment of test and training set molecules. CoMFA and CoMSIA models were found statistically significant with leave-one-out correlation coefficients (q ²) of 0.816 and 0.838, respectively; cross-validated coefficients ($r_{\text{cv}}^{2}$) of 0.812 and 0.837, respectively; and conventional coefficients (r ²) of 0.969 and 0.966, respectively. QSAR models were validated by a test set of 14 compounds giving satisfactory prediction of correlation coefficients ($r_{\text{pred}}^{2}$) of 0.910 and 0.904 for CoMFA and CoMSIA models, respectively. Based on the generated contour maps, we have designed 10 novel ALK inhibitors and predicted their activities. Finally, molecular docking study was performed for designed molecules. The designed compounds showed good potential to be used as ALK inhibitors.