【摘要】 研究了37个环已烯类神经氨酸酶抑制剂结构与其抗流感活性的定量构效关系。采用本实验室提出的三维原子场全息作用矢量对环已烯类神经氨酸酶抑制剂进行结构参数化表征,采用逐步回归对变量进行筛选后运用偏最小二乘回归建模。训练集模型的复相关系数（R²）、交互校验复相关系数(Q_cum²)和拟合均方根误差（RMSEE）分别为0.862,0.575和0.4864,预测集RMSEP为0.4435,模型具有良好稳定性和预测能力。结果表明三维原子场全息作用矢量能较好表征该类分子结构信息,值得进一步推广应用。更多还原

【Abstract】 The quantitative structure-activity relationship（QSAR） of 37 cyclohexene influenza neuraminidase inhibitors was studied.A newly developed three-dimensional holographic vector of atomic interaction field （3D-HoVAIF） was used to describe the chemical structures of cyclohexene influenza neuraminidase inhibitors.After the structural characterization,the descriptors obtained were screened by step-wise multiple regression（SMR） then a model of 3D-HoVAIF descriptors and cyclohexene influenza neuraminidase inhibitors’ activities were built with partial least square regression（PLS）.The obtained model of training set with the cumulative multiple correlation coefficient （R²）,cumulative cross-validated(Q_cum²) and the Root Mean Square Error of Estimation（RMSEE） were 0.862,0.575 and 0.4864 respectively.The Root Mean Square Error of Prediction（RMSEP） of test set was 0.4435.It shows that the model had favorable stability and good prediction capability,and the 3D-HoVAIF is able to characterized the steric information efficiently,and this method is worthy of widespiead application.更多还原