田家豪, 王亮亮, 潘里, 丁俊杰, 丁晓琴. 基于量化反应性指数的氨基甲酸酯类农药定量构效关系研究[J]. 农药学学报, 2021, 23(4): 688-693. DOI: 10.16801/j.issn.1008-7303.2021.0095
    引用本文: 田家豪, 王亮亮, 潘里, 丁俊杰, 丁晓琴. 基于量化反应性指数的氨基甲酸酯类农药定量构效关系研究[J]. 农药学学报, 2021, 23(4): 688-693. DOI: 10.16801/j.issn.1008-7303.2021.0095
    TIAN Jiahao, WANG Liangliang, PAN Li, DING Junjie, DING Xiaoqin. Quantitative structure-activity relationship of carbamate pesticides based on quantitative reactivity index[J]. Chinese Journal of Pesticide Science, 2021, 23(4): 688-693. DOI: 10.16801/j.issn.1008-7303.2021.0095
    Citation: TIAN Jiahao, WANG Liangliang, PAN Li, DING Junjie, DING Xiaoqin. Quantitative structure-activity relationship of carbamate pesticides based on quantitative reactivity index[J]. Chinese Journal of Pesticide Science, 2021, 23(4): 688-693. DOI: 10.16801/j.issn.1008-7303.2021.0095

    基于量化反应性指数的氨基甲酸酯类农药定量构效关系研究

    Quantitative structure-activity relationship of carbamate pesticides based on quantitative reactivity index

    • 摘要: 氨基甲酸酯类农药被广泛用于农业生产中,其作用机理主要是通过与乙酰胆碱酯酶共价结合,从而抑制其正常的生物活性,但此类农药的无节制使用导致其大量残留于生态环境中,对整个生态系统的生存安全造成了严重威胁。本文作者基于量化反应性指数,采用遗传/偏最小二乘法,对氨基甲酸酯与其对乙酰胆碱酯酶的抑制活性进行了定量构效关系研究。结果表明:预测方程的决定系数 (R2) 均在0.8以上,采用留一法和自举法交叉验证的R2均在0.7以上;一致性模型的R2为0.823,均方根误差为0.369,获得了较好的预测模型。同时发现,量化反应性指数的引入有效增强了模型的可解释性,有助于进一步探索和验证氨基甲酸酯与乙酰胆碱酯酶的作用机理。本文所得到的模型可为氨基甲酸酯类农药的活性预测和风险评估提供理论依据。

       

      Abstract: Carbamate compounds are widely used in agricultural production. Their mechanism of action is mainly through the covalent bonding with acetylcholinesterase, which will, inhibit its normal biological activity. The abuse of such pesticides has resulted in large amounts of them remaining in the ecological environment, posing a serious threat to the survival safety of the entire ecosystem. In this work, the genetic/partial least squares method was used to study the quantitative structure-activity relationship between carbamate compounds and their acetylcholinesterase inhibitory potency based on the quantitative reactivity index. The calculation results showed that the determination coefficients (R2) of the prediction equations were all above 0.8, and the R2 of the leave-one-out method and the bootstrap method were all above 0.7. The R2 of the consensus model was 0.823, and the root mean square error was 0.369. In addition, the introduction of the quantitative reactivity index effectively enhanced the interpretation performance of the model, which was helpful to explore and verify the mechanism of action of carbamate and acetylcholinesterase. The model obtained in this work can provide a theoretical basis for the activity prediction and risk assessment of such dangerous compounds.

       

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