Akbari Somaye, Zebardast Tannaz, Zarghi Afshin, Hajimahdi Zahra
Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical Chemistry, Pharmaceutical Sciences Branch, Islamic Azad University, Tehran, Iran (IAUPS).
Department of Medicinal Chemistry, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Iran J Pharm Res. 2017 Spring;16(2):525-532.
COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure-activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R) of 0.972 and 0.531 for training and test groups, respectively. The quality of the model was evaluated by leave-one-out (LOO) cross validation (LOO correlation coefficient (Q) of 0.943) and Y-randomization. We also employed a leverage approach for the defining of applicability domain of model. Based on QSAR models results, COX-2 inhibitory activity of selected data set had correlation with BEHm6 (highest eigenvalue n. 6 of Burden matrix/weighted by atomic masses), Mor03u (signal 03/unweighted) and IVDE (Mean information content on the vertex degree equality) descriptors which derived from their structures.
采用逐步多元线性回归（SW-MLR）方法，通过定量构效关系（QSAR）对一些1,4-二氢吡啶和5-氧代-1,4,5,6,7,8-六氢喹啉衍生物的COX-2抑制活性进行建模。所建立的模型稳健且具有预测性，训练组和测试组的相关系数（R）分别为0.972和0.531。通过留一法（LOO）交叉验证（LOO相关系数（Q）为0.943）和Y随机化对模型质量进行评估。我们还采用了杠杆方法来定义模型的适用范围。基于QSAR模型结果，所选数据集的COX-2抑制活性与从其结构衍生的BEHm6（Burden矩阵的最高特征值n. 6/按原子质量加权）、Mor03u（信号03/未加权）和IVDE（顶点度相等的平均信息含量）描述符相关。
