[1]冯长君,堵锡华,沐来龙.用新型连接性指数与神经网络预测取代苯酚和取代苯甲酸生物降解性[J].南京理工大学学报(自然科学版),2009,(05):700-706.
 FENG Chang-jun,DU Xi-hua,MU Lai-long.Prediction of Biodegradability of Substituted Phenols and Benzoic Acids with Novel Molecular Connectivity Index and Artificial Neural Network[J].Journal of Nanjing University of Science and Technology,2009,(05):700-706.
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用新型连接性指数与神经网络预测取代苯酚和取代苯甲酸生物降解性
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
期数:
2009年05期
页码:
700-706
栏目:
出版日期:
2009-10-30

文章信息/Info

Title:
Prediction of Biodegradability of Substituted Phenols and Benzoic Acids with Novel Molecular Connectivity Index and Artificial Neural Network
作者:
冯长君 1 堵锡华 1 沐来龙 2
1. 徐州工程学院化学化工学院,江苏徐州221008; 2. 徐州师范大学化学化工学院, 江苏徐州221116
Author(s):
FENG Chang-jun1DU Xi-hua1MU Lai-long2
1.School of Chemistry and Chemical Engineering,Xuzhou Institute of Technology,Xuzhou 221008,China;2.School of Chemistry and Chemical Engineering,Xuzhou Normal University,Xuzhou 221116,China
关键词:
分子连接性指数 取代苯酚 取代苯甲酸 生化需氧量 人工神经网络 定量结构-生物降解相关性
Keywords:
molecular connectivity index substituted phenol substituted benzoic acid biochemical oxygen demand artificial neural network quantitative structure-biodegradability relationship
分类号:
X172;X592
摘要:
基于Kier和Hall的分子连接性指数及邻接矩阵,定义新型分子连接性指数mKvt,并计算了30种取代苯酚和取代苯甲酸的分子连接性指数。经最佳变量子集回归建立了25种有机污染物生化需氧量(BOD)与2Kpv、5Kpv的定量结构-生物降解相关性(QSBR)模型,该模型判定系数R2、逐一剔除法(LOO)的交互验证系数Q2及Kubinyi函数(FIT)分别为0.818、0.776和3.410,该模型具有高度的稳定性及良好预测能力。据此模型可知,影响有机污染物BOD的主要因素是取代基的电子效应以及分子的柔韧性、折叠
Abstract:
On the basis of the revision of Kier and Hall’s molecular connectivity index and conjugation matrix,a novel molecular connectivity indexmKvt is defined and calculated for 30 substituted phenol and benzoic acid molecules in this paper.The quantitative structure-biodegradability relationship(QSBR) model between biochemical oxygen demand(BOD) and 2Kvp,5Kvp for 25 organic pollutants among above molecules is developed by Leaps-and-Bounds regression(LBR),the traditional correlation coefficient R2,the cross-validation correlation coefficient Q2 of leave-one-out(LOO) and Kubinyi function(FIT) are 0.818,0.776 and 3.410,respectively.The result demonstrates that the model is highly reliable and has good predictive ability from the point of statistics.The model shows that the dominant influencing factors of BOD are the electronic effects of substituents and the space factors of molecule: the flexibility and the puckered degree of molecules.The two structural parameters are used as the input neurons of the artificial neural network,and a 2∶5∶1 network architecture is employed.A satisfying QSBR model can be constructed with the back-propagation algorithm,with the correlation coefficient R2 and the standard errors being 0.967 and 3.688,respectively,showing that the relationship between BOD and the two structural parameters has a good nonlinear correlation.The results show that the new molecular connectivity index have good rationality and efficiency for the biochemical oxygen demand of organic compounds.It can be expected that the mKvt will be used widely in quantitative structure-property/activity relationship research.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家自然科学基金( 20776149);环境模拟与污染控制国家重点联合实验室基金(KJ2007001); 江苏省高校自然科学基金( 08KJD610003);徐州工程学院培育课题(XKY2008313)
作者简介: 冯长君( 1954- ), 男,教授, 主要研究方向:物质构效学, E-mail:fengc@j xzit. edu. cn。
更新日期/Last Update: 2012-11-19