酚类化合物麻醉毒性的CoFMA研究

冯惠, 石春玲, 李靖, 周俊, 冯长君. 酚类化合物麻醉毒性的CoFMA研究[J]. 生态毒理学报, 2021, 16(3): 340-346. doi: 10.7524/AJE.1673-5897.20200208001
引用本文: 冯惠, 石春玲, 李靖, 周俊, 冯长君. 酚类化合物麻醉毒性的CoFMA研究[J]. 生态毒理学报, 2021, 16(3): 340-346. doi: 10.7524/AJE.1673-5897.20200208001
Feng Hui, Shi Chunling, Li Jing, Zhou Jun, Feng Changjun. CoMFA Study on Polar Narcosis Toxicity of Phenols[J]. Asian Journal of Ecotoxicology, 2021, 16(3): 340-346. doi: 10.7524/AJE.1673-5897.20200208001
Citation: Feng Hui, Shi Chunling, Li Jing, Zhou Jun, Feng Changjun. CoMFA Study on Polar Narcosis Toxicity of Phenols[J]. Asian Journal of Ecotoxicology, 2021, 16(3): 340-346. doi: 10.7524/AJE.1673-5897.20200208001

酚类化合物麻醉毒性的CoFMA研究

    作者简介: 冯惠(1985-),女,博士研究生,讲师,研究方向为环境污染物构效学,E-mail:fenghuixzjs@sina.com
    通讯作者: 冯长君, E-mail: fengcj@xzit.edu.cn
  • 基金项目:

    结构化学国家重点实验室开放基金资助项目(2016028);江苏省大学生创新创业训练项目(xcx2020143)

  • 中图分类号: X171.5

CoMFA Study on Polar Narcosis Toxicity of Phenols

    Corresponding author: Feng Changjun, fengcj@xzit.edu.cn
  • Fund Project:
  • 摘要: 通过比较分子力场分析方法(CoMFA)建立酚类化合物对梨形四膜虫极性麻醉毒性(pT)的三维定量结构-活性相关(3D-QSAR)模型。基于训练集41个化合物建立了预测模型,10个化合物作为验证集(含模板分子)。训练集的CoMFA模型显示立体场、静电场对麻醉毒性贡献依次为53.9%和46.1%。其交叉验证相关系数(Rcv2)为0.735,非交叉验证相关系数(R2)为0.971。对训练集、测试集中的化合物麻醉毒性进行预测,显示出较强的稳定性和良好的预测能力。根据CoMFA模型的立体场和静电场三维等势线图可知,在羟基的间、对位上引入小体积基团,以及邻、对位有负电性基团,有利于提高酚类衍生物的麻醉毒性。基于此,设计了7种具有更高麻醉毒性的酚类化合物,有待生物医学实验验证。
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  • 收稿日期:  2020-02-08

酚类化合物麻醉毒性的CoFMA研究

    通讯作者: 冯长君, E-mail: fengcj@xzit.edu.cn
    作者简介: 冯惠(1985-),女,博士研究生,讲师,研究方向为环境污染物构效学,E-mail:fenghuixzjs@sina.com
  • 徐州工程学院化学化工学院, 徐州 221018
基金项目:

结构化学国家重点实验室开放基金资助项目(2016028);江苏省大学生创新创业训练项目(xcx2020143)

摘要: 通过比较分子力场分析方法(CoMFA)建立酚类化合物对梨形四膜虫极性麻醉毒性(pT)的三维定量结构-活性相关(3D-QSAR)模型。基于训练集41个化合物建立了预测模型,10个化合物作为验证集(含模板分子)。训练集的CoMFA模型显示立体场、静电场对麻醉毒性贡献依次为53.9%和46.1%。其交叉验证相关系数(Rcv2)为0.735,非交叉验证相关系数(R2)为0.971。对训练集、测试集中的化合物麻醉毒性进行预测,显示出较强的稳定性和良好的预测能力。根据CoMFA模型的立体场和静电场三维等势线图可知,在羟基的间、对位上引入小体积基团,以及邻、对位有负电性基团,有利于提高酚类衍生物的麻醉毒性。基于此,设计了7种具有更高麻醉毒性的酚类化合物,有待生物医学实验验证。

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