QSAR studies on imidazothienopyrazines as IKK-β inhibitors: from 2D to 3D

• Published in: Journal of chemometrics 2009-06, Vol.23 (6), p.304-314
• Main Authors: Long, Wei, Liu, Peixun, Li, Xinru, Xu, Yang, Yu, Jie, Ma, Shitang, Yu, Lingling, Zou, Zhongmei
• Format: Article
• Language: English
• Subjects: Chemistry; Exact sciences and technology; General and physical chemistry; General. Nomenclature, chemical documentation, computer chemistry; IKK-β inhibitors; imidazothienopyrazines; Phase; QSAR; SVM; Theory of reactions, general kinetics. Catalysis. Nomenclature, chemical documentation, computer chemistry
• ISSN: 0886-9383; 1099-128X
• DOI: 10.1002/cem.1235

This paper presents the investigation of quantitative structure‐activity relationship (QSAR) for imidazothienopyrazines from 2D to 3D, for assistance of developing new IKK‐β inhibitors. In 2D‐QSAR, we built linear and nonlinear models by heuristic method (HM) and Support Vector Machine (SVM) methods, respectively. The results (R2HM(training set) = 0.8775, R2SVM(training set) = 0.9356, R2HM(test set) = 0.6452, R2SVM(test set) = 0.8736) showed that the nonlinear model is more precise to predict the activities of imidazothienopyrazines. In 3D‐QSAR, Phase methodology was employed, resulting in a successful model for prediction of imidazothienopyrazines' bioactivities, and this model (R2(training set) = 0.9717, R2(test set) = 0.9209) is better than any one of 2D‐QSAR models, linear or nonlinear. In addition, the discussion of 2D descriptors from 2D‐QSAR and the 3D plots from Phase results provided suggestions and guidance to develop new compounds which may present better bioactivities against IKK‐β. Copyright © 2009 John Wiley & Sons, Ltd. This paper presents the investigation of QSAR for imidazothienopyrazines from 2D to 3D, for assistance of developing new IKK‐β inhibitors. In 2D‐QSAR, we built linear and nonlinear models by HM and SVM methods, respectively. The results showed that the nonlinear model is more precise to predict the activities of imidazothienopyrazines. In 3D‐QSAR, Phase methodology was employed, resulting in a successful model for prediction of imidazothienopyrazines' bioactivities, and this model is better than any one of 2D‐QSAR models.