Discovery of novel indoleaminopyrimidine NIK inhibitors based on molecular docking-based support vector regression (SVR) model.

Graphical abstract Highlights • The integration of docking scores, key interaction profiles remarkably improved the accuracy of the QSAR models. • The established MD-SVR (Molecular Docking Based SVM regression) model was applied on designing new NIK inhibitors. • The identified compounds would be promising leads for finding highly potent NIK inhibitors. Abstract A set of NF-κB-inducing kinase (NIK) inhibitors was used to develop a molecular docking-based QSAR model by using nonlinear regression method. The accuracy of the QSAR model was remarkably improved by integrating the docking scores and key interaction profiles. Two indole-aminopyrimidine derivatives 32a and 32b predicted as NIK inhibitors were synthesized and biologically evaluated. The significant correlationship between experimental data and MD-SVR model-predicted results were observed. The binding mode of 32a and 32b with NIK were further investigated by dynamic simulations. Compound 32b was proposed as a promising lead for the findings of highly potent inhibitors. [ABSTRACT FROM AUTHOR]