Riahi Siavash, Pourbasheer Eslam, Dinarvand Rassoul, Ganjali Mohammad Reza, Norouzi Parviz
Institute of Petroleum Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran.
Chem Biol Drug Des. 2008 Dec;72(6):575-84. doi: 10.1111/j.1747-0285.2008.00739.x.
Quantitative structure-activity relationship of the 2-(1-propylpiperidin-4-yl)-1H-benzimidazole-4-carboxamide as a potent inhibitor of poly(ADP-ribose) polymerase for cancer treatment was studied. A suitable set of molecular descriptors was calculated and the genetic algorithm was employed to select those descriptors that resulted in the best fitted models. Excellent results were obtained employing multiple linear regressions and critically discussed using a variety of statistical parameters. Furthermore, the model was validated using leave-one-out and leave-group-out cross-validation, external test set and chance correlation. A genetic algorithm-multiple linear regression model with seven selected descriptors was obtained. This model, with high statistical significance (R(2) = 0.935, Q(2)(LOO)= 0.894, Q(2)(LGO)= 0.875, F = 53.481), could be used to predict poly(ADP-ribose) polymerase inhibitor activity of the molecules.
研究了2-(1-丙基哌啶-4-基)-1H-苯并咪唑-4-甲酰胺作为一种用于癌症治疗的聚(ADP-核糖)聚合酶强效抑制剂的定量构效关系。计算了一组合适的分子描述符，并采用遗传算法选择那些能产生最佳拟合模型的描述符。使用多元线性回归获得了优异的结果，并使用各种统计参数进行了严格讨论。此外，该模型通过留一法和留组法交叉验证、外部测试集和随机相关性进行了验证。得到了一个具有七个选定描述符的遗传算法-多元线性回归模型。该模型具有较高的统计显著性（R(2)=0.935，Q(2)(LOO)=0.894，Q(2)(LGO)=0.875，F = 53.481），可用于预测分子的聚(ADP-核糖)聚合酶抑制剂活性。
