Bitlis Eren University, Science and Art Faculty, Department of Chemistry, Bitlis, Turkey.
SAR QSAR Environ Res. 2011 Jun;22(3):217-38. doi: 10.1080/1062936X.2010.548341.
The electron conformational-genetic algorithm (EC-GA), a sophisticated hybrid approach combining the GA and EC methods, has been employed for a 4D-QSAR procedure to identify the pharmacophore for benzotriazines as sarcoma inhibitors and for quantitative prediction of activity. The calculated geometry and electronic structure parameters of every atom and bond of each molecule are arranged in a matrix described as the electron-conformational matrix of contiguity (ECMC). By comparing the ECMC of one of the most active compounds with other ECMCs we were able to obtain the features of the pharmacophore responsible for the activity, as submatrices of the template known as electron conformational submatrices of activity. The GA was used to select the most important descriptors and to predict the theoretical activity of training and test sets. The predictivity of the model was internally validated. The best QSAR model was selected, having r² = 0.9008, standard error = 0.0510 and cross-validated squared correlation coefficient, q² = 0.8192.
电子构象遗传算法（EC-GA）是一种结合遗传算法和电子结构方法的复杂混合方法，已被用于 4D-QSAR 程序，以确定苯并三嗪作为肉瘤抑制剂的药效团，并对活性进行定量预测。每个分子中每个原子和键的计算几何和电子结构参数排列在一个矩阵中，称为电子构象连续性矩阵（ECMC）。通过比较最活跃化合物之一的 ECMC 与其他 ECMCs，我们能够获得负责活性的药效团的特征，作为已知为活性的电子构象子矩阵的模板的子矩阵。遗传算法用于选择最重要的描述符，并预测训练集和测试集的理论活性。模型的预测能力进行了内部验证。选择了最佳的 QSAR 模型，其 r² = 0.9008，标准误差 = 0.0510，交叉验证平方相关系数 q² = 0.8192。
