高级搜索

羟基自由基反应常数定量预测模型

,  ,  ,  , 

downloadPDF

上一篇

下一篇

范德玲, 刘济宁, 王蕾, 周林军, 石利利. 羟基自由基反应常数定量预测模型[J]. 环境化学, 2015, 34(10): 1924-1931. doi: 10.7524/j.issn.0254-6108.2015.10.2015032605
引用本文: 范德玲, 刘济宁, 王蕾, 周林军, 石利利. 羟基自由基反应常数定量预测模型[J]. 环境化学, 2015, 34(10): 1924-1931. doi: 10.7524/j.issn.0254-6108.2015.10.2015032605
shu
FAN Deling, LIU Jining, WANG Lei, ZHOU Linjun, SHI Lili. QSAR model for predicting hydroxyl radical reaction constant of organic chemicals[J]. Environmental Chemistry, 2015, 34(10): 1924-1931. doi: 10.7524/j.issn.0254-6108.2015.10.2015032605
Citation: FAN Deling, LIU Jining, WANG Lei, ZHOU Linjun, SHI Lili. QSAR model for predicting hydroxyl radical reaction constant of organic chemicals[J]. Environmental Chemistry, 2015, 34(10): 1924-1931. doi: 10.7524/j.issn.0254-6108.2015.10.2015032605
shu

羟基自由基反应常数定量预测模型

  • 1.

    环保部南京环境科学研究所, 南京, 210042

  • 基金项目:

    国家高技术研究发展计划(863计划)(2013AA060A308)

    环保公益性行业科研专项经费(2013467028)资助.

QSAR model for predicting hydroxyl radical reaction constant of organic chemicals

  • 1.

    Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing, 210042, China

  • Fund Project:

  • 摘要: 羟基自由基(·OH)反应常数对于表征有机污染物在大气环境中持久性具有重要意义.依据经济合作与发展组织(OECD)关于QSAR模型构建与验证的导则, 采用量子化学方法对覆盖了不同种类的722个化合物进行结构优化, 遗传算法筛选最优结构描述符, 运用多元线性回归构建化学品羟基自由基反应常数预测模型.拟合结果显示, 多元线性回归模型决定系数R2和标准误差分别为0.819和0.508, 基于leverage法评价模型的应用域, 结果表明模型具有较强的稳健性、预测性和拟合能力.美国环保局EPI Suite中AOPWIN模块羟基自由基反应常数预测模型没有给出明确的应用域, 利用所建模型与美国EPI Suite对化学物质进行比较, 其中, 有85个化学物质预测优于EPI Suite软件.通过定量结构-活性关系(QSAR)预测技术可弥补羟基自由基反应常数测试数据的缺失, 减少测试费用和评估数据的不确定性.
    Abstract: Reaction rate constants of hydroxyl radicals (kOH) are of vital importance for assessing the persistence of organic pollutants in the atmosphere. 722 chemicals were optimized by quantum chemistry method and screened by genetic algorithm for optimal descriptors. A quantitative structure-activity relationship (QSAR) model for hydroxyl radical reaction constant was developed by employing multiple linear regression (MLR) according to the QSAR model development and validation guideline issued by Organization for Economic Cooperation and Development (OECD). The QSAR modeling results indicated that the R2 and SE of multiple linear regressions model were 0.819 and 0.508, The application domain was evaluated based on the leverage method. The results showed that the model had high goodness-of-fit, robustness and good predictive ability. The hydroxyl radical reaction constant prediction model in AOPWIN module of the EPI Suite software did not have a definite application domain and the prediction of 85 chemicals was better than EPI software Suite. Thus, the QSAR model can be employed to make up the missing data, redue the cost of testing and evaluated of data uncertainty.
  • 加载中
  • [1] Brown V J. Reaching for chemicals safety [J]. Environmental Health Perspectives, 2003, 111:A766-A769
    [2] Sabljic A, Peijnenburg W. Modeling lifetime and degradability of organic compounds in air, soil, and water systems (IUPAC Technical Report)[J]. Pure and Applied Chemistry, 2001, 73:1331-1348
    [3] Organisation for Economic Co-operation and Development (OECD), Guidance document on the validation of (quantitative) structure activity relationships models, Technical Report for OECD Environment, Health and Safety Publications Series on Testing and Assessmen No. 69: Paris, 2007
    [4] Atkinson R. Estimation of gas-phase hydroxyl radical rate constants for organic chemicals[J]. Environmental toxicology and chemistry, 1988, 7 (6):435-442
    [5] Klamt A. Estimation of gas-phase hydroxyl radical rate constants of organic compounds from molecular orbital calculations[J]. Chemosphere, 1993, 26 (7): 1273-1289
    [6] Kwok E S, Atkinson R. Estimation of hydroxyl radical reaction rate constants for gas-phase organic compounds using a structure-reactivity relationship: An update[J]. Atmospheric Environment, 1995, 29 (14):1685-1695
    [7] Gramatica P, Pilutti P, Papa E. Validated QSAR prediction of OH tropospheric degradation of VOCs: Splitting into training-test sets and consensus modeling[J]. Journal of chemical information and computer sciences, 2004, 44 (5):1794-1802
    [8] Öberg T. A QSAR for the hydroxyl radical reaction rate constant: Validation, domain of application, and prediction[J]. Atmospheric Environment, 2005, 39 (12): 2189-2200
    [9] Fatemi M, Baher E. Quantitative structure-property relationship modelling of the degradability rate constant of alkenes by OH radicals in atmosphere[J]. SAR and QSAR in Environmental Research, 2009, 20 (1-2): 77-90
    [10] Meylan W M, Howard P H. A review of quantitative structure-activity relationship methods for the prediction of atmospheric oxidation of organic chemicals[J]. Environmental Toxicology and Chemistry, 2003, 22: 1724-1732
    [11] Wang Y N, Chen J W, Li X H, et al. Predicting rate constants of hydroxyl radical reactions with organic pollutants: Algorithm, validation, applicability domain, and mechanistic interpretation[J]. Atmospheric Environment, 2009, 43 (5), 1131-1135
    [12] Kennard R W, Stone L A. Computer Aided Design of Experiments[J]. Technometrics, 1969, 11 (1):137-148
    [13] Mauri A, Consonni V, Pavan M, et al. DRAGON software: An easy approach to molecular descriptor calculations[J]. Match, 2006, 56, 237-248
    [14] Todeschini R, Consonni V. Handbook of Molecular Descriptors[M]. Weilheim:Wiley-VCH, 2008
    [15] Liu H, Gramatica P. QSAR study of selective ligands for the thyroid hormone receptor beta[J]. Bioorganic and Medicinal Chemistry, 2007, 15:5251-5261
    [16] Lei B, Ma Y, Li J, et al. Prediction of the adsorption capability onto activated carbon of a large data set of chemicals by local lazy regression method[J]. Atmospheric Environment, 2010, 44: 2954-2960
    [17] Cho S J, Hermsmeier M A. Genetic algorithm guided selection: Variable selection and subset selection[J].Journal of Chemical Information and Computer Sciences, 2002, 42 (4):927-936
    [18] Puzyn T, Falandysz J. Computational estimation of logarithm of N-octanol/air partition coefficient and subcooled vapor pressures of 75 chloronaphthalene congeners[J]. Atmospheric Environment, 2005, 39 (8): 1439-1446
    [19] Tropsha A, Gramatica P, Gombar V K. The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models[J]. QSAR and Combinatorial Science, 2003, 22: 69-77
    [20] Pompe M, Veber M, Randic' M, et al. Using variable and fixed topological indices for the prediction of reaction rate constants of volatile unsaturated hydrocarbons with OH radicals[J]. Molecules, 2004, 9(12): 1160-1176
  • 加载中
WeChat 点击查看大图
计量
  • 文章访问数:  1207
  • HTML全文浏览数:  1122
  • PDF下载数:  548
  • 施引文献:  0
出版历程
  • 收稿日期:  2015-03-26
  • 刊出日期:  2015-10-15
范德玲, 刘济宁, 王蕾, 周林军, 石利利. 羟基自由基反应常数定量预测模型[J]. 环境化学, 2015, 34(10): 1924-1931. doi: 10.7524/j.issn.0254-6108.2015.10.2015032605
引用本文: 范德玲, 刘济宁, 王蕾, 周林军, 石利利. 羟基自由基反应常数定量预测模型[J]. 环境化学, 2015, 34(10): 1924-1931. doi: 10.7524/j.issn.0254-6108.2015.10.2015032605
shu
FAN Deling, LIU Jining, WANG Lei, ZHOU Linjun, SHI Lili. QSAR model for predicting hydroxyl radical reaction constant of organic chemicals[J]. Environmental Chemistry, 2015, 34(10): 1924-1931. doi: 10.7524/j.issn.0254-6108.2015.10.2015032605
Citation: FAN Deling, LIU Jining, WANG Lei, ZHOU Linjun, SHI Lili. QSAR model for predicting hydroxyl radical reaction constant of organic chemicals[J]. Environmental Chemistry, 2015, 34(10): 1924-1931. doi: 10.7524/j.issn.0254-6108.2015.10.2015032605
shu

羟基自由基反应常数定量预测模型

  • 1. 环保部南京环境科学研究所, 南京, 210042
  • 收稿日期:  2015-03-26
基金项目:

国家高技术研究发展计划(863计划)(2013AA060A308)

环保公益性行业科研专项经费(2013467028)资助.

摘要: 羟基自由基(·OH)反应常数对于表征有机污染物在大气环境中持久性具有重要意义.依据经济合作与发展组织(OECD)关于QSAR模型构建与验证的导则, 采用量子化学方法对覆盖了不同种类的722个化合物进行结构优化, 遗传算法筛选最优结构描述符, 运用多元线性回归构建化学品羟基自由基反应常数预测模型.拟合结果显示, 多元线性回归模型决定系数R2和标准误差分别为0.819和0.508, 基于leverage法评价模型的应用域, 结果表明模型具有较强的稳健性、预测性和拟合能力.美国环保局EPI Suite中AOPWIN模块羟基自由基反应常数预测模型没有给出明确的应用域, 利用所建模型与美国EPI Suite对化学物质进行比较, 其中, 有85个化学物质预测优于EPI Suite软件.通过定量结构-活性关系(QSAR)预测技术可弥补羟基自由基反应常数测试数据的缺失, 减少测试费用和评估数据的不确定性.

English Abstract

    全文HTML

参考文献 (20)

返回顶部

目录

/

返回文章
返回

Copyright © 2019 中国科学院生态环境研究中心