论文部分内容阅读
采用量子化学中的密度泛函理论方法,在B3LYP/6-31++G水平下,系统计算了11种亚苄丙二腈类衍生物的量子化学参数,并通过回归分析方法,构建了二维定量构效模型,分析了影响活性抑制的主要因素,并建立了亚苄丙二腈衍生物与抑制酪氨酸激酶活性之间的定量构效关系方程,研究结果表明:该类化合物分子的分子总能量ET与疏水性参数log P对抑制活性的影响最大,且疏水性能越强,分子的活性抑制能力越高。在此基础上,使用留一法交叉验证了模型的预测能力,结果表明,模型的回归系数和留一法交叉验证系数分别为0.796和0.7291,表明模型具有较好的预测能力,可以用于预测此类化合物的活性。基于结构相似性,设计了4种新型的亚苄丙二腈类衍生物分子,在相同水平下计算其量子化学参数,并预测其活性,结果表明这些新型新型酪氨酸激酶抑制剂均具有较好的活性,研究结果为进一步设计性能更好的酪氨酸激酶抑制剂提供了理论参考。
The quantum chemistry parameters of 11 kinds of benzalmalononitriles derivatives were systematically calculated by B3LYP / 6-31 ++ G level using the density functional theory method in quantum chemistry. By regression analysis, Dimensional quantitative structure-activity model, the main factors that affect the inhibition of the activity were analyzed, and the quantitative structure-activity relationship equation between the benzylidenemalononitrile derivatives and the tyrosine kinase inhibition activity was established. The results show that: The total molecular energy ET and hydrophobic parameter log P have the greatest effect on the inhibitory activity, and the stronger the hydrophobic property, the higher the activity inhibition ability of the molecule. On the basis of this, the predictive ability of the model is verified by using the one-leave-only method. The results show that the regression coefficients of the model and the one-legged cross-validation coefficient are 0.796 and 0.7291 respectively, indicating that the model has good predictive ability and can be used for prediction The activity of such compounds. Based on structural similarity, four novel benzalononitrile derivatives were designed and their quantum chemical parameters were calculated at the same level, and their activity was predicted. The results showed that these novelty tyrosine kinase inhibitors all had higher Good activity, the results provide a theoretical reference for the further design of tyrosine kinase inhibitors with better performance.