An initial structure-activity relationship study of the novel necroptosis inhibitor Nec-21 was described. Any changes of the tetracyclic scaffold were detrimental for the activity. Introduction of a substituent to 7 or 8 position (e.g., cyano or methoxy group, respectively), would increase the activity. The 7 and 8-position disubstituted compound 17 b was 35-fold as potent as the lead, while EC50 reached 14 nM.

01 Mar 2012·Journal of Molecular ModelingQ4 · CHEMISTRY

Probing the structural requirements of A-type Aurora kinase inhibitors using 3D-QSAR and molecular docking analysis

Q4 · CHEMISTRY

Article

Author: Xia Wang ; Yan Li ; Yong-hua Wang ; Hui-xiao Zhang

Aurora-A, the most widely studied isoform of Aurora kinase overexpressed aberrantly in a wide variety of tumors, has been implicated in early mitotic entry, degradation of natural tumor suppressor p53 and centrosome maturation and separation; hence, potent inhibitors of Aurora-A may be therapeutically useful drugs in the treatment of various forms of cancer. Here, we report an in silico study on a group of 220 reported Aurora-A inhibitors with six different substructures. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques on this series of molecules. The resultant optimum 3D-QSAR models exhibited an r (cv) (2) value of 0.404-0.582 and their predictive ability was validated using an independent test set, ending in r (pred) (2) 0.512-0.985. In addition, docking studies were employed to explore these protein-inhibitor interactions at the molecular level. The results of 3D-QSAR and docking analyses validated each other, and the key structural requirements affecting Aurora-A inhibitory activities, and the influential amino acids involved were identified. To the best of our knowledge, this is the first report on 3D-QSAR modeling of Aurora-A inhibitors, and the results can be used to accurately predict the binding affinity of related analogues and also facilitate the rational design of novel inhibitors with more potent biological activities.

01 Apr 2011·Bioorganic & Medicinal Chemistry Letters

Prediction of biological activity of Aurora-A kinase inhibitors by multilinear regression analysis and support vector machine

Article

Author: Chong, Yang ; Wang, Liyu ; Hu, Xiaoying ; Wang, Kai ; Yan, Aixia

Several QSAR (quantitative structure-activity relationships) models for predicting the inhibitory activity of 117 Aurora-A kinase inhibitors were developed. The whole dataset was split into a training set and a test set based on two different methods, (1) by a random selection; and (2) on the basis of a Kohonen's self-organizing map (SOM). Then the inhibitory activity of 117 Aurora-A kinase inhibitors was predicted using multilinear regression (MLR) analysis and support vector machine (SVM) methods, respectively. For the two MLR models and the two SVM models, for the test sets, the correlation coefficients of over 0.92 were achieved.

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