中国药物警戒 ›› 2019, Vol. 16 ›› Issue (6): 321-324.

• 基础与临床研究 •    下一篇

吡咯里西啶类生物碱基因毒性的构效关系研究

刘凯利1, 梁经纬1, 王珊1, 李佐静2, 闫心丽2, 孟繁浩1,*   

  1. 1中国医科大学药学院,辽宁 沈阳110122;
    2沈阳药科大学医疗器械学院,辽宁 沈阳110016
  • 收稿日期:2019-07-12 修回日期:2019-07-12 出版日期:2019-06-20 发布日期:2019-07-12
  • 通讯作者: 孟繁浩,男,博士生导师,教授,药物毒性研究。E-mail: fhmeng@cmu.edu.cn
  • 作者简介:刘凯利,男,在读硕士,药物构效关系相关研究。
  • 基金资助:
    国家自然科学基金项目（81573687; 81303315; 81274182）：基于HSP90的乌头二萜生物碱构效关系与靶向毒效机制研究; 药学统计学在中药代谢组学中生物标记物识别的研究; 生物碱毒性作用靶点的识别及预测系统的研究

Study on the Quantitative Structure-genetic Toxicity Relationships of Pyrrolizidine Alkaloids

LIU Kaili1, LIANG Jingwei1, WANG San1, LI Zuojing2, YAN Xinli2, MENG Fanhao1,*   

  1. 1 School of Pharmacy, China Medical University, Liaoning Shenyang 110122, China;
    2 School of Medical Devices, Shenyang Pharmaceutical University, Liaoning Shenyang 110016, China
  • Received:2019-07-12 Revised:2019-07-12 Online:2019-06-20 Published:2019-07-12

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摘要： 目的 以基因毒性数据（暴露浓度,CI）作为自变量建立模型,并利用该模型预测了吡咯里西啶类生物碱的基因毒性。方法 本文采用偏最小二乘回归法对吡咯里西啶类生物碱的基因毒性进行预测研究。结果 本文采用了PLS进行降维,进行8个成分的提取及建模,通过QSAR分析,得到吡咯里西啶类化合物的基因毒性预测模型如下：Log(toxi)=SAA*0.790049-SAG*0.141402-VOL*0.0830882+LogP*1.75971- RE*0.345487-POLAR*0.369259-TE*0.119995-BE*0.0987964-IAE*0.849541-EE*0.129214+CCI*0.0239072-HOF*0.097627-DIPOLE*0.0134722。结论 本研究所建立的QSAR模型具有较好的毒性预测能力。

关键词: 吡咯里西啶类生物碱, 偏最小二乘回归法, 基因毒性, 构效关系

Abstract: Objective To establish a model using genotoxicity data (exposure level, CI) as the independent variable and predict the genetic toxicity of pyrrolizidine alkaloids using the model. Methods The partial least squares method was adopted to conduct a predictive study on the genetic toxicity of pyrrolizidine alkaloids. Results Partial least squares method (PLS) was applied to reduce the dimension, 8 components were extracted and a model was built using the 8 components. The prediction model of genetic toxicity of pyrrolizidine alkaloids is obtained through quantitative structure activity relationships (QSAR) analysis. The model is as follows: Log(toxi)=SAA*0.790049-SAG*0.141402-VOL*0.0830882+LogP*1.75971-RE*0.345487-POLAR*0.369259-TE*0.119995-BE*0.0987964-IAE*0.849541-EE*0.129214+CCI*0.0239072-HOF*0.097627-DIPOLE*0.0134722. Conclusion The QSAR model established in this study has good prediction ability for toxicity.

Key words: pyrrolizidine alkaloids, partial least squares method, genetic toxicity, quantitative structure activity relationships

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