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支持向量机法用于4-芳基-4氢-苯并比喃化合物的凋亡诱导活性研究

Support vector machine applied to research the apoptosis-inducing activity of 4-aryl-4H-chromenes compounds

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【作者】 韩光喜张蕊余成关宏宇葛春华张向东

【Author】 HAN Guang-xi,ZHANG Rui,YU Cheng,GUAN Hong-yu,GE Chun-hua,ZHANG Xiang-dong(Department of Chemistry,Liaoning University Science and Engineering,Shengyang 110036,China)

【机构】 辽宁大学化学院

【摘要】 通过计算获得了39个4-芳基-4氢-苯并吡喃化合物的11个结构特征参数,应用逐步线性回归方法对参数进行筛选.并用支持向量回归(SVR)算法,对4-芳基-4氢-苯并吡喃化合物与其凋亡诱导活性进行定量构效关系(QSAR)研究.通过核函数参数的优化,建立了预测模型,训练集和预测集的实验值与计算值的平方相关系数R2分别为0.997和0.893.研究结果表明,支持向量回归算法可用于小样本数的药物分子设计研究,以合成具有更高生物活性的新药物.

【Abstract】 Support vector machines algorithm was applied to study the quantitative structure-activity relationship of 39 apoptosis-inducing 4-aryl-4H-chromenes.The eleven kinds of molecular characteristic parameters were calculated and optimized by stepwise multiple regression.A more predictive model was set up through optimizing kernel function parameters.The squared correlation coefficient(R2) values between experimental versus calculated values for 30 molecules in the training set and 9 molecules in the test set are 0.997 and 0.893,respectively.The satisfactory results showed that support vector regression algorithm would be well used for drug molecules design.

【基金】 辽宁省科技厅资助项目(2008S104)
  • 【文献出处】 分子科学学报 ,Journal of Molecular Science , 编辑部邮箱 ,2009年04期
  • 【分类号】R914
  • 【被引频次】3
  • 【下载频次】113
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