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利用量子化学密度泛函理论(DFT)中的杂化泛函B3LYP对三个系列60个喹啉环取代的喜树碱衍生物(CPTs)进行了构型优化,在6-311+G(d,p)基组下计算出相应的电子结构参数;采用逐步多元回归方法对各组化合物建立了几个新的分子描述符与抗癌活性之间的定量结构-活性关系(QSAR)模型,探讨了影响化合物抗癌活性的主要结构因素及其作用机理.结果表明,所得QSAR模型具有良好的预测能力,影响药物活性的主要因素有分子极化率和原子净电荷以及最高占据分子轨道能量.根据所建最佳QSAR可以较准确地预测喜树碱类衍生物的抗癌活性,这有助于未来设计合成新型高效抗癌喜树碱类似物以及改进和完善其作用机理.
Three series of 60 quinoline ring substituted camptothecin derivatives (CPTs) were optimized by hybrid functional B3LYP in quantum chemical density functional theory (DFT) , p), the corresponding electronic structure parameters were calculated. The QSAR model of several new molecular descriptors and anti-cancer activity was established by stepwise multiple regression The main structural factors that affect the anticancer activity of the compounds and their mechanism of action were studied.The results showed that the QSAR model obtained had good predictive ability.The main factors influencing the activity of the compounds were molecular polarizability and net atomic charge as well as the highest occupied molecular orbital energy.According to The best QSAR can predict the anticancer activity of camptothecin derivatives more accurately, which will help us to design and synthesize new and effective anticancer camptothecin analogues in the future and to improve and perfect its mechanism of action.