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Different molecular fragments were endued with different fragments weights. In order to test whether or not the mfVCI could be used for predicting different properties of the same molecules, the Quantitative Structure-Property Relationship (QSPR) models of aqueous solubility (Sw) and n-octanol/water partition coefficients(Kow) for 36 halogenated benzenes based on the mfVCI were investigated. The fitting goodness of the QSPR models are mainly characterized by determination coefficient (R2), standard deviation (SD), Fischer variance ratio(F), and significant lever (P). The internal cross-validation including leave-one-out and leave-many-out methods with cross-validated correlation coefficients (qloo2 and qlmo2) was used to evaluate the model's robustness. The external cross-validation was used to evaluate the predictive power of the models developed from the training set by correlation coefficients (qext2). The linear relationship was assumed between mfVCI and Sw or Kow in here. The mfVCI was optimized by using Solver. The target function is the root mean calculated residual sum of squares for training set. The QSPR models with R2 value of more than 0.97, q2 value of more than 0.89, and qext2 value of more than 0.95 have the good robustness and predictive ability as well as fitting ability. The mfVCI could distinguish the different role of same atoms or functional groups among different chemical bonding. The results show that the mfVCI could be well used in the prediction of both of aqueous solubility and n-octanol/water partition coefficients for halogenated benzenes. It could describe different properties equally well. The mfVCI maybe play an important role in the development of molecular descriptors on QSPR researches., authors=CHEN Qiang, SUN Jingmin, HU Liang, authorsList=CHEN Qiang;SUN Jingmin;HU Liang, authorCompany=College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=J6YOUW5HWdteOgVfRcC2Aw==, pdfFileSize=780599, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242127484372713489, articleId=1242127481247956993, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=可变连接性指数预测卤代苯溶解度及分配系数, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=分子片段是因成键环境不同而具有不同特性的原子或官能团,也可以认为是影响化合物性质的一个分子结构单元。分子片段可变连接性指数(mfVCI)是定量结构-性质相关(QSPR)研究中的一种拓扑描述符。为了检验mfVCI对同组化合物不同性质预测的适用性,本文建立了mfVCI与36个卤代苯的水溶解度(Sw)和正辛醇/水分配系数(Kow)的线性QSPR模型,用规划求解方法得到最优解,并采用拟合优度诊断和交互验证法(内部交互验证和外部交互验证)对模型进行检验。结果表明,所建立的模型均具有较好的拟合能力(R2>0.97)和稳健性(q2>0.89),且预测能力强(qext2>0.95)。mfVCI除具有一般可变分子连接性指数的优势外,还能更好地区分不同成键环境中原子或官能团对同组化合物不同性质的影响,能较好地应用于卤代苯的水溶解度及分配系数的预测。, authors=陈强, 孙敬敏, 胡亮, authorsList=陈强;孙敬敏;胡亮, authorCompany=兰州大学大气科学学院,兰州 730000, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=7eHgw5Lw4fGmBtv6ZI8woA==, pdfFileSize=780599, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null)}, 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可变连接性指数预测卤代苯溶解度及分配系数
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陈强;孙敬敏;胡亮
科技导报 | 研究论文 2011,29(15): 58-61
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科技导报 |研究论文 2011 , 29 (15) : 58 -61
可变连接性指数预测卤代苯溶解度及分配系数
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陈强;孙敬敏;胡亮
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Prediction of Aqueous Solubility and Partition Coefficients of Halogenated Benzenes Using Molecular Fragments Variable Connectivity Index
CHEN Qiang;SUN Jingmin;HU Liang
Affiliations
    College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
出版时间: 2011-05-28 doi: 10.3981/j.issn.1000-7857.2011.15.006
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分子片段是因成键环境不同而具有不同特性的原子或官能团,也可以认为是影响化合物性质的一个分子结构单元。分子片段可变连接性指数(mfVCI)是定量结构-性质相关(QSPR)研究中的一种拓扑描述符。为了检验mfVCI对同组化合物不同性质预测的适用性,本文建立了mfVCI与36个卤代苯的水溶解度(Sw)和正辛醇/水分配系数(Kow)的线性QSPR模型,用规划求解方法得到最优解,并采用拟合优度诊断和交互验证法(内部交互验证和外部交互验证)对模型进行检验。结果表明,所建立的模型均具有较好的拟合能力(R2>0.97)和稳健性(q2>0.89),且预测能力强(qext2>0.95)。mfVCI除具有一般可变分子连接性指数的优势外,还能更好地区分不同成键环境中原子或官能团对同组化合物不同性质的影响,能较好地应用于卤代苯的水溶解度及分配系数的预测。
分子片段可变连接性指数  /  QSPR  /  水溶解度  /  正辛醇/水分配系数  /  卤代苯
For the molecular fragments Variable Connectivity Index (mfVCI), the molecular fragments are defined as the atoms or functional groups and are also regarded as the molecular structure unit for the major influence of the property. Different molecular fragments were endued with different fragments weights. In order to test whether or not the mfVCI could be used for predicting different properties of the same molecules, the Quantitative Structure-Property Relationship (QSPR) models of aqueous solubility (Sw) and n-octanol/water partition coefficients(Kow) for 36 halogenated benzenes based on the mfVCI were investigated. The fitting goodness of the QSPR models are mainly characterized by determination coefficient (R2), standard deviation (SD), Fischer variance ratio(F), and significant lever (P). The internal cross-validation including leave-one-out and leave-many-out methods with cross-validated correlation coefficients (qloo2 and qlmo2) was used to evaluate the model's robustness. The external cross-validation was used to evaluate the predictive power of the models developed from the training set by correlation coefficients (qext2). The linear relationship was assumed between mfVCI and Sw or Kow in here. The mfVCI was optimized by using Solver. The target function is the root mean calculated residual sum of squares for training set. The QSPR models with R2 value of more than 0.97, q2 value of more than 0.89, and qext2 value of more than 0.95 have the good robustness and predictive ability as well as fitting ability. The mfVCI could distinguish the different role of same atoms or functional groups among different chemical bonding. The results show that the mfVCI could be well used in the prediction of both of aqueous solubility and n-octanol/water partition coefficients for halogenated benzenes. It could describe different properties equally well. The mfVCI maybe play an important role in the development of molecular descriptors on QSPR researches.
mfVCI  /  QSPR  /  aqueous solubility  /  octanol/water partition coefficient  /  halogenated benzene
陈强;孙敬敏;胡亮. 可变连接性指数预测卤代苯溶解度及分配系数. 科技导报, 2011 , 29 (15) : 58 -61 . DOI: 10.3981/j.issn.1000-7857.2011.15.006
CHEN Qiang;SUN Jingmin;HU Liang. Prediction of Aqueous Solubility and Partition Coefficients of Halogenated Benzenes Using Molecular Fragments Variable Connectivity Index[J]. Science & Technology Review, 2011 , 29 (15) : 58 -61 . DOI: 10.3981/j.issn.1000-7857.2011.15.006

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2011年第29卷第15期
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doi: 10.3981/j.issn.1000-7857.2011.15.006
  • 接收时间:2011-01-10
  • 首发时间:2011-05-28
  • 出版时间:2011-05-28
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  • 收稿日期:2011-01-10
  • 修回日期:2011-03-25
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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