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

• Published in: Chemical physics letters Vol. 718; pp. 38 - 45
• Main Authors: Ye, Qing, Li, Qiu, Gao, Anhui, Ying, Huazhou, Cheng, Gang, Chen, Jing, Che, Jinxin, Li, Jia, Dong, Xiaowu, Zhou, Yubo
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2019
• ISSN: 0009-2614; 1873-4448
• DOI: 10.1016/j.cplett.2019.01.031

[Display omitted] •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. 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.