柳爱平, 王晓光, 陈灿, 刘兴平, 陆爱军, 黄明智, 刘钊杰, 姚建仁. 新型肟醚化合物杀叶蝉活性的CoMFA研究[J]. 农药学学报, 2005, 7(1): 14-18.
    引用本文: 柳爱平, 王晓光, 陈灿, 刘兴平, 陆爱军, 黄明智, 刘钊杰, 姚建仁. 新型肟醚化合物杀叶蝉活性的CoMFA研究[J]. 农药学学报, 2005, 7(1): 14-18.
    LIU Ai-ping, WANG Xiao-guang, CHEN Can, LIU Xing-ping, LU Ai-jun, HUANG Ming-zhi, LIU Zhao-jie, YAO Jian-ren. CoMFA Study on Insecticidal Activityof Novel Oxime-ethers against Nephotettix cincticeps[J]. Chinese Journal of Pesticide Science, 2005, 7(1): 14-18.
    Citation: LIU Ai-ping, WANG Xiao-guang, CHEN Can, LIU Xing-ping, LU Ai-jun, HUANG Ming-zhi, LIU Zhao-jie, YAO Jian-ren. CoMFA Study on Insecticidal Activityof Novel Oxime-ethers against Nephotettix cincticeps[J]. Chinese Journal of Pesticide Science, 2005, 7(1): 14-18.

    新型肟醚化合物杀叶蝉活性的CoMFA研究

    CoMFA Study on Insecticidal Activityof Novel Oxime-ethers against Nephotettix cincticeps

    • 摘要: 用比较分子力场分析(CoMFA)方法对28个间苯氧基苄醇肟醚和30个联苯苄醇肟醚化合物杀叶蝉Nephotettix cincticeps活性的定量构效关系进行了研究。分别研究了上述两类化合物及其综合的QSAR模型,3种QSAR模型都表明肟苯环对位取代基是影响化合物杀叶蝉活性的主要因素,其体积和电性增加有利于提高化合物的杀叶蝉活性。比较3种模型,还发现综合模型为最佳预测模型,其交叉验证系数R2cv=0.628,非交叉验证的相关系数R2=0.971,标准偏差SE=0.109,F=133.84。用此模型预测了检验组10个化合物的 -lgLC50,结果满意。所得QSAR模型可为进一步合成更高活性的化合物提供指导。

       

      Abstract: The quantitative structure activity relationship (QSAR) of the insecticidal activities of 28 m-phenoxybenzyl oxime-ethers and 30 biphenylbenzyl oxime-ethers against Nephotettix cincticeps using comparative molecular field analysis (CoMFA) method was investigated. Separate studies of QSAR models on each set of compounds and whole set of compounds were carried out. Three models show that p-substituent on phenyl ring of oxime moiety is the main factor affecting the activity. The larger volume and stronger electricity p-substituent has, the higher activity the compound has. By comparing these 3 models, it is found that the integrated model shows a higher ability to predict the activities of these oxime-ethers than other models, crossvalidated R2cv=0.628, non-crossvalidated R2=0.971, standard error(SE)=0.109, F=133.84. The integrated model also shows a high ability to predict the biological activity(-lgLC50) for 10 testing set compounds. QSAR models will give some guidance on synthesizing compounds with enhanced activities.

       

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