摘要
基于Chem3D Ultra 7.0软件中的MOPAC半经验方法 AM1,计算了13种呋虫胺衍生物的19个量子化学和理化参数(包括ELUMO、EHOMO、△E=ELUMO-EHOMO、QC1、QC2、QN、QN1~QN4、QO、QO、μ、Hf、Ve、E0、Cv、Sm等)。采用最佳变量子集回归方法,建立呋虫胺衍生物对褐飞虱杀虫活性与上述结构参数的定量构效关系模型。结果表明,呋虫胺衍生物对褐飞虱杀虫活性的大小与ELUMO、QN1呈负相关,而与QC2正相关。所建的最优三变量模型具有良好的预报能力(R2=0.928、Rcv2=0.805、Rcv-22=0.797)和较高的稳健性(Radj2、F、VIF、t、AIC和FIT等检验)。设计与预测了4种新颖化合物的杀虫活性,在浓度为500mg/dm3下,它们的杀虫活性预测值均超过115%。所建模型可为化学工作者合成新型高效新烟碱类化合物提供理论参考。
The nineteen quantum-chemical and physical chemical parameters including ELUMO , ErtoMo , Δ E = ELUMO-EHOMO, QC1, QC2, QN, QN1 - QN4, Qo, Qo, μ, Hf, Vc, Eo, Cv, Sm, and so on of thirteen dinotefuran derivates were calculated by MOPAC-AM1 method in Chem3D Ultra 7.0 software. The QSAR model between the insecticidal activity of dinotefuran derivates to Planthoppers and the above nineteen descriptors was established by leaps-and-bounds regression. The parameters of ELUMO , QC2 and QNI had important contributions to the insecticidal effects of fluorinated phenols. There was a remarkable negative correlation between the insecticidal activity of dinotefuran derivates to Planthopp^rs for ELUMO and QN~, respectively, and a significant positive correlation between the insecticidal activity of dinotefuran derivates to Planthoppers for Qc2. The optimal model of three variables had good R 2 predicting ability （ R2 = 0. 928, Rcv2 = 0. 805 , Rev_22 = 0. 797 ） and stability （ Rdj = 0. 904 , F = 38. 487 and VIF., t, AIC, Fly） for all investigated compounds. The insecticidal activity parameters of four new compounds were predicted using QSAR models, all of them were disclosed to have better insecticidal activity （the insecticidal activity is over 100% when concentration is 500mg·dm-3）. The model can provide theoretical reference for the design of new neonicotinoid compounds.
出处
《化学通报》
CAS
CSCD
北大核心
2014年第6期545-549,共5页
Chemistry
基金
国家自然科学基金项目(21075138)
环境模拟与污染控制国家重点联合实验室开放基金项目(13K02ESPCT)
徐州市科技计划研究项目(XM13B111
XZZD1104)资助
关键词
新烟碱
呋虫胺衍生物
褐飞虱
杀虫活性
构效关系
Neonicotinoid, Dinotefuran derivate, Planthoppers, Insecticidal activity, Quantitative structure-activity relationship （QSAR）
