QSAR studies on pyrazole-4-carboxamide derivatives as Aurora A kinase inhibitors

Evaluation of Substituted Pyrazole-Based Kinase Inhibitors in One Decade (2011-2020): Current Status and Future Prospects

Pyrazole has been recognized as a pharmacologically important privileged scaffold whose derivatives produce almost all types of pharmacological activities and have attracted much attention in the last decades. Of the various pyrazole derivatives reported as potential therapeutic agents, this article focuses on pyrazole-based kinase inhibitors. Pyrazole-possessing kinase inhibitors play a crucial role in various disease areas, especially in many cancer types such as lymphoma, breast cancer, melanoma, cervical cancer, and others in addition to inflammation and neurodegenerative disorders. In this article, we reviewed the structural and biological characteristics of the pyrazole derivatives recently reported as kinase inhibitors and classified them according to their target kinases in a chronological order. We reviewed the reports including pyrazole derivatives as kinase inhibitors published during the past decade (2011-2020).

2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors

Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q² = 0.565 (cross-validated correlation coefficient) and r² = 0.888 (non-cross-validated correlation coefficient) was built to predict the activity of EGFR inhibitors. The mean absolute error (MAE) of the training set and test set was 0.308 log units and 0.526 log units, respectively. In addition, molecular docking was also employed to investigate the interaction between EGFR inhibitors and EGFR.