Polychlorinated dibenzothiophenes（PCDTs） are classified as persistent organic pollutants in the environment,so the analysis of PCDTs by their gas chromatographic behaviors is of great significance.Quantitative struc...Polychlorinated dibenzothiophenes（PCDTs） are classified as persistent organic pollutants in the environment,so the analysis of PCDTs by their gas chromatographic behaviors is of great significance.Quantitative structure-retention relationship（QSRR） analysis is a useful technique capable of relating chromatographic retention time to the molecular structure.In this paper,a QSRR study of 37 PCDTs was carried out by using molecular electronegativity distance vector（MEDV） descriptors and multiple linear regression（MLR） and partial least-squares regression（PLS） methods.The correlation coefficient R of established MLR,PLS models,leave-one-out（LOO） cross-validation（CV）,Q2ext were 0.9951,0.9942,0.9839（MLR） and 0.9925,0.9915,0.9833（PLS）,respectively.Results showed that the model exhibited excellent estimate capability for internal sample set and good predictive capability for external sample set.By using MEDV descriptors,the QSRR model can provide a simple and rapid way to predict the gas-chromatographic retention indices of polychlorinated dibenzothiophenes in conditions of lacking standard samples or poor experimental conditions.展开更多
A molecular electronegativity distance vector(M)based on 13 atomic types has been used to describe the structures of 19 conjugates(LHCc)of levofloxacin-thiadiazole HDAC inhibitor(HDACi)and related inhibitory activitie...A molecular electronegativity distance vector(M)based on 13 atomic types has been used to describe the structures of 19 conjugates(LHCc)of levofloxacin-thiadiazole HDAC inhibitor(HDACi)and related inhibitory activities(pH,i=1,2,6)of LHCc against histone deacetylases(HDACs,such as HDAC1,HDAC2 and HDAC6).The quantitative structure-activity relationships(QSAR)were established by using leaps-and-bounds regression analysis for the inhibitory activities(pH)of 19 above compounds to HDAC1,HDAC2 and HDAC6 along with M.The correlation coefficients(R~2)and the leave-one-out(LOO)cross validation Rfor the pH,pHand pHmodels were 0.976 and 0.949;0.985 and 0.977;0.976 and 0.932,respectively.The QSAR models had favorable correlations,as well as robustness and good prediction capability by R~2,F,R~2,A,Fand Vtests.Validated by using 3876 training sets,the models have good external prediction ability.The results indicate that the molecular structural units:–CH–(g=1,2),–NH,–OH,=O,–O–and–S–are the main factors which can affect the inhibitory activity of pH,pHas well as pHbioactivities of these compounds directly.Accordingly,the main interactions between HDACs inhibitor and HDACs are hydrophobic interaction,hydrogen bond,and coordination with Znto form compounds,which is consistent with the results in reports.展开更多
Quantum chemistry parameters of 28 alkyl（1-phenylsulfonyl） cycloalkane-carboxy-lates were computed at the 6-31G＊ level in fully optimal manner using B3LYP method of density functional theory （DFT）. With GQSARF2.0...Quantum chemistry parameters of 28 alkyl（1-phenylsulfonyl） cycloalkane-carboxy-lates were computed at the 6-31G＊ level in fully optimal manner using B3LYP method of density functional theory （DFT）. With GQSARF2.0 program, the correlation equations that can predict n-octanol/water partition coefficient （lgKow） were developed using the structural and thermodynamic parameters of 28 alkyl（1-phenylsulfonyl） cycloalkane-carboxylates with experimental data of lgKow as theoretical descriptors; the correlation coefficient （R^2） was 0.9452 and the cross-validation squared correlation coefficient （Rcv^2） 0.9312. Furthermore, a four-variable model from MEDV was obtained, of which R2 = 0.9497 and Rov^2 =0.9388. The models were validated by variance inflation factor （VIF） and t-test. Cross-validation indicates that the correlation and predicting ability of the model based on both DFT method and MEDV are more advantageous than those obtained from semi-empirical AM1 method.展开更多
Molecular structures of reactants were characterized by molecular electronegativity distance vector （VHMED） considering hydrogen association. A reasonable molecular modeling equation with 4-parameters was achieved f...Molecular structures of reactants were characterized by molecular electronegativity distance vector （VHMED） considering hydrogen association. A reasonable molecular modeling equation with 4-parameters was achieved for quantitative structure-property/activity relationship （QSPR/QSAR） by stepwise multiple regression （SMR） that the variable was introduced item by item in significant level order. A high correlation coefficient （R = 0.980） demonstrates that the model is able to well express a quantitative relation between stereoselectivity and the reactant structures as quantitative structure-reactivity/stereoselectivity relationship （QSRR/QSSR）. The multiple correlation coefficient （Rcv= 0.964） was tested through cross-validation with the leave-one-out （LOO） procedure. The above results show that the model possesses high estimation stability and good prediction ability between the amount of both cis and trans isomers in products and reactants.展开更多
Using the molecular electronegativity distance vector descriptors derived directly from the molecular topological structures, the relative retention time （RRT） of polybrominated diphenyl ethers （PBDEs） were predic...Using the molecular electronegativity distance vector descriptors derived directly from the molecular topological structures, the relative retention time （RRT） of polybrominated diphenyl ethers （PBDEs） were predicted. A four-variable regression model （M30） with the correlation coefficient of 0.9816 and the root mean square errors of 0.061 was developed using a training set including 30 PBDEs. The correlation coefficient of 0.9841 and the root mean square errors of 0.054 between the values of RRT predicted by M30 and the RRT observed for 16 external PBDEs show a good predictive potential of M30. The descriptors included in the M30 represent four interactions between four pairs of atom types, i.e., atom -C= and -C=, -C= and 〉C=, 〉C= and 〉C=, -C= and -Br.展开更多
A molecular electronegativity distance vector based on 13 atomic types (MEDV-13) is used to describe the structures of 62 polychlorinated naphthalene (PCN) congeners and related to the gas chromatographic relative ret...A molecular electronegativity distance vector based on 13 atomic types (MEDV-13) is used to describe the structures of 62 polychlorinated naphthalene (PCN) congeners and related to the gas chromatographic relative retention indices (RIs) of PCNs. Using multiple linear regression, a 4-variable quantitative structure-retention relationship (QSRR) with the correlation coefficient of estimations (r) being 0.9912 and the root mean square error of estimations (RMSEE) being 31.4 and the correlation coefficient of predictions (q) and the root mean square error of predictions (RMSEP) in the leave-one-out procedure are 0.9898 and 33.76, respectively.展开更多
The molecular electronegativity distance vector（MEDV） was applied to characterize the molecular structures of 30 organophosphorous compounds. Optimum MEDV descriptors were selected by using the variable selection an...The molecular electronegativity distance vector（MEDV） was applied to characterize the molecular structures of 30 organophosphorous compounds. Optimum MEDV descriptors were selected by using the variable selection and modeling method based on the prediction（VSMP） technique. The quantitative structure-toxicity relationship（QSTR） model was built for acute toxicity（96h pLC50） of organophosphorous compounds to steelhead. The developed QSTR model with strictly internal and external validations presents relatively high correlation coefficient（R2） of 0.9518, leave-one-out（LOO） cross-validated correlation coefficient（Q2LOO） of 0.9355, and leave-many-out（LMO） cross-validated correlation coefficient（Q2LMO） of 0.9290. The robustness of the model was confirmed by the y-randomization test（R2yrand = 0.0772 and Q2 yrand = –0.5313） and bootstrapping（R2bstr = 0.9502 and Q2 bstr = 0.9177） method. The result of external validation, Q2F1 = 0.9336, Q2F2 = 0.9336, Q2F3 = 0.9447, r2 m = 0.8120, and CCC = 0.9602, shows that the QSTR model has a high predictive ability.展开更多
Using the molecular electronegativity distance vector descriptors derived directly from the molecular topological structures, the aqueous solubilities of polychlorinated biphenyls (PCBs) were predicted. A three-variab...Using the molecular electronegativity distance vector descriptors derived directly from the molecular topological structures, the aqueous solubilities of polychlorinated biphenyls (PCBs) were predicted. A three-variable regression equation with correlation coefficient of 0.9739 and the root mean square errors of 0.26 was developed. The descriptors included in the equation represent three interactions between three pairs of atomic types, i.e., atom -C= and >C=, -C= and -Cl, and -Cl and -Cl. It has been proved that the aqueous solubilities of 137 PCB congeners can be accurately predicted as long as there are more than 65 calibration compounds.展开更多
A novel atomic electronegative distance vector (AEDV) has been developed to express the chemical environment of various chemically equivalent carbon atoms in alcohols and alkanes. Combining AEDV and γ parameter, four...A novel atomic electronegative distance vector (AEDV) has been developed to express the chemical environment of various chemically equivalent carbon atoms in alcohols and alkanes. Combining AEDV and γ parameter, four five-parameter linear relationship equations of chemical shift for four types of carbon atom are created by using multiple linear regression. Correlation coefficients are R = 0.9887, 0.9972, 0.9918 and 0.9968 end roots of mean square error are RMS = 0.906, 0. 821, 1.091 and 1.091 of four types of carbons, i.e., type 1, 2, 3, and 4 for primary, secondary, tertiary, and quaternary carbons, respectively. The stability and prediction capacity for external samples of four models have been tested by cross-validation.展开更多
Selective inhibition of cyclooxygenase-2 (COX-2) might avoid the side effects of current available nonsteroidal antiinflammatory drugs while retaining their therapeutic efficacy. A novel variable selection and modelin...Selective inhibition of cyclooxygenase-2 (COX-2) might avoid the side effects of current available nonsteroidal antiinflammatory drugs while retaining their therapeutic efficacy. A novel variable selection and modeling method based on prediction is developed to construct the quantitative structure-activity relationships (QSAR) between the molecular electronegativity distance vector (MEDV) based on 13 atomic types and the biological activities of a set of selective cyclooxygenase-2 inhibitory molecules,3,4-diarylcycloxazolones (DAA) plus indomethacin,naproxen,and celecoxib. Using multiple linear regression,a 5-variable linear model is developed with the calibrated correlation coefficient of 0.9271 and root mean square error of 0.17 in modeling stage and the validated correlation coefficient of 0.9030 and root mean square error of 0.20 in leave-one-out validation step,respectively. To further test the predictive ability of the model,20 DAA compounds are picked up to construct a training set which is used to build a QSAR model and then the model is employed to predict the biological activities of the balance compounds. The predicted correlation coefficient and root mean square error are 0.9332 and 0.19, respectively.展开更多
基金supported by the Foundation of Returned Scholars (Main Program) of Shanxi Province (200902)
文摘Polychlorinated dibenzothiophenes（PCDTs） are classified as persistent organic pollutants in the environment,so the analysis of PCDTs by their gas chromatographic behaviors is of great significance.Quantitative structure-retention relationship（QSRR） analysis is a useful technique capable of relating chromatographic retention time to the molecular structure.In this paper,a QSRR study of 37 PCDTs was carried out by using molecular electronegativity distance vector（MEDV） descriptors and multiple linear regression（MLR） and partial least-squares regression（PLS） methods.The correlation coefficient R of established MLR,PLS models,leave-one-out（LOO） cross-validation（CV）,Q2ext were 0.9951,0.9942,0.9839（MLR） and 0.9925,0.9915,0.9833（PLS）,respectively.Results showed that the model exhibited excellent estimate capability for internal sample set and good predictive capability for external sample set.By using MEDV descriptors,the QSRR model can provide a simple and rapid way to predict the gas-chromatographic retention indices of polychlorinated dibenzothiophenes in conditions of lacking standard samples or poor experimental conditions.
基金supported by the National Natural Science Foundation of China(21473081,21075138)special fund of State Key Laboratory of Structure Chemistry(20160028)
文摘A molecular electronegativity distance vector(M)based on 13 atomic types has been used to describe the structures of 19 conjugates(LHCc)of levofloxacin-thiadiazole HDAC inhibitor(HDACi)and related inhibitory activities(pH,i=1,2,6)of LHCc against histone deacetylases(HDACs,such as HDAC1,HDAC2 and HDAC6).The quantitative structure-activity relationships(QSAR)were established by using leaps-and-bounds regression analysis for the inhibitory activities(pH)of 19 above compounds to HDAC1,HDAC2 and HDAC6 along with M.The correlation coefficients(R~2)and the leave-one-out(LOO)cross validation Rfor the pH,pHand pHmodels were 0.976 and 0.949;0.985 and 0.977;0.976 and 0.932,respectively.The QSAR models had favorable correlations,as well as robustness and good prediction capability by R~2,F,R~2,A,Fand Vtests.Validated by using 3876 training sets,the models have good external prediction ability.The results indicate that the molecular structural units:–CH–(g=1,2),–NH,–OH,=O,–O–and–S–are the main factors which can affect the inhibitory activity of pH,pHas well as pHbioactivities of these compounds directly.Accordingly,the main interactions between HDACs inhibitor and HDACs are hydrophobic interaction,hydrogen bond,and coordination with Znto form compounds,which is consistent with the results in reports.
基金Supported by the Key Program of National Natural Science Foundation of China (No. 20737001)the National Science Foundation for Post-doctoral Scientists of China (No. 2003033486)
文摘Quantum chemistry parameters of 28 alkyl（1-phenylsulfonyl） cycloalkane-carboxy-lates were computed at the 6-31G＊ level in fully optimal manner using B3LYP method of density functional theory （DFT）. With GQSARF2.0 program, the correlation equations that can predict n-octanol/water partition coefficient （lgKow） were developed using the structural and thermodynamic parameters of 28 alkyl（1-phenylsulfonyl） cycloalkane-carboxylates with experimental data of lgKow as theoretical descriptors; the correlation coefficient （R^2） was 0.9452 and the cross-validation squared correlation coefficient （Rcv^2） 0.9312. Furthermore, a four-variable model from MEDV was obtained, of which R2 = 0.9497 and Rov^2 =0.9388. The models were validated by variance inflation factor （VIF） and t-test. Cross-validation indicates that the correlation and predicting ability of the model based on both DFT method and MEDV are more advantageous than those obtained from semi-empirical AM1 method.
文摘Molecular structures of reactants were characterized by molecular electronegativity distance vector （VHMED） considering hydrogen association. A reasonable molecular modeling equation with 4-parameters was achieved for quantitative structure-property/activity relationship （QSPR/QSAR） by stepwise multiple regression （SMR） that the variable was introduced item by item in significant level order. A high correlation coefficient （R = 0.980） demonstrates that the model is able to well express a quantitative relation between stereoselectivity and the reactant structures as quantitative structure-reactivity/stereoselectivity relationship （QSRR/QSSR）. The multiple correlation coefficient （Rcv= 0.964） was tested through cross-validation with the leave-one-out （LOO） procedure. The above results show that the model possesses high estimation stability and good prediction ability between the amount of both cis and trans isomers in products and reactants.
基金the National Basic Research Program of China(2003CB415002)the National Natural Science Foundation of China(No.20377022) the Guangxi Natural Science Fund(No.0236063)for their financial supports.
文摘Using the molecular electronegativity distance vector descriptors derived directly from the molecular topological structures, the relative retention time （RRT） of polybrominated diphenyl ethers （PBDEs） were predicted. A four-variable regression model （M30） with the correlation coefficient of 0.9816 and the root mean square errors of 0.061 was developed using a training set including 30 PBDEs. The correlation coefficient of 0.9841 and the root mean square errors of 0.054 between the values of RRT predicted by M30 and the RRT observed for 16 external PBDEs show a good predictive potential of M30. The descriptors included in the M30 represent four interactions between four pairs of atom types, i.e., atom -C= and -C=, -C= and 〉C=, 〉C= and 〉C=, -C= and -Br.
基金We are especially grateful to the China Postdoctoral Science Foundation and the National High Technology Project of China (No. 2001AA640601) for their financial supports.
文摘A molecular electronegativity distance vector based on 13 atomic types (MEDV-13) is used to describe the structures of 62 polychlorinated naphthalene (PCN) congeners and related to the gas chromatographic relative retention indices (RIs) of PCNs. Using multiple linear regression, a 4-variable quantitative structure-retention relationship (QSRR) with the correlation coefficient of estimations (r) being 0.9912 and the root mean square error of estimations (RMSEE) being 31.4 and the correlation coefficient of predictions (q) and the root mean square error of predictions (RMSEP) in the leave-one-out procedure are 0.9898 and 33.76, respectively.
基金the financial support from the National Natural Science Foundation of China(21207024 and 21407032)the Provincial Natural Science Foundation of Guangxi(2014GXNSFAA118060,2014GXNSFBA118233 and 2013GXNSFBA019228)
文摘The molecular electronegativity distance vector（MEDV） was applied to characterize the molecular structures of 30 organophosphorous compounds. Optimum MEDV descriptors were selected by using the variable selection and modeling method based on the prediction（VSMP） technique. The quantitative structure-toxicity relationship（QSTR） model was built for acute toxicity（96h pLC50） of organophosphorous compounds to steelhead. The developed QSTR model with strictly internal and external validations presents relatively high correlation coefficient（R2） of 0.9518, leave-one-out（LOO） cross-validated correlation coefficient（Q2LOO） of 0.9355, and leave-many-out（LMO） cross-validated correlation coefficient（Q2LMO） of 0.9290. The robustness of the model was confirmed by the y-randomization test（R2yrand = 0.0772 and Q2 yrand = –0.5313） and bootstrapping（R2bstr = 0.9502 and Q2 bstr = 0.9177） method. The result of external validation, Q2F1 = 0.9336, Q2F2 = 0.9336, Q2F3 = 0.9447, r2 m = 0.8120, and CCC = 0.9602, shows that the QSTR model has a high predictive ability.
文摘Using the molecular electronegativity distance vector descriptors derived directly from the molecular topological structures, the aqueous solubilities of polychlorinated biphenyls (PCBs) were predicted. A three-variable regression equation with correlation coefficient of 0.9739 and the root mean square errors of 0.26 was developed. The descriptors included in the equation represent three interactions between three pairs of atomic types, i.e., atom -C= and >C=, -C= and -Cl, and -Cl and -Cl. It has been proved that the aqueous solubilities of 137 PCB congeners can be accurately predicted as long as there are more than 65 calibration compounds.
基金Project supported by Ministry of Education "Chunhui Program" and Fok Ying Tung Education Foundation.
文摘A novel atomic electronegative distance vector (AEDV) has been developed to express the chemical environment of various chemically equivalent carbon atoms in alcohols and alkanes. Combining AEDV and γ parameter, four five-parameter linear relationship equations of chemical shift for four types of carbon atom are created by using multiple linear regression. Correlation coefficients are R = 0.9887, 0.9972, 0.9918 and 0.9968 end roots of mean square error are RMS = 0.906, 0. 821, 1.091 and 1.091 of four types of carbons, i.e., type 1, 2, 3, and 4 for primary, secondary, tertiary, and quaternary carbons, respectively. The stability and prediction capacity for external samples of four models have been tested by cross-validation.
基金ProjectsupportedbytheNationalHighTechnologyResearchandDevelopmentProgramofChina (No .2 0 0 1AA64 60 10 4)andtheNa tionalNaturalScienceFoundationofChina (No .2 0 1770 0 8)
文摘Selective inhibition of cyclooxygenase-2 (COX-2) might avoid the side effects of current available nonsteroidal antiinflammatory drugs while retaining their therapeutic efficacy. A novel variable selection and modeling method based on prediction is developed to construct the quantitative structure-activity relationships (QSAR) between the molecular electronegativity distance vector (MEDV) based on 13 atomic types and the biological activities of a set of selective cyclooxygenase-2 inhibitory molecules,3,4-diarylcycloxazolones (DAA) plus indomethacin,naproxen,and celecoxib. Using multiple linear regression,a 5-variable linear model is developed with the calibrated correlation coefficient of 0.9271 and root mean square error of 0.17 in modeling stage and the validated correlation coefficient of 0.9030 and root mean square error of 0.20 in leave-one-out validation step,respectively. To further test the predictive ability of the model,20 DAA compounds are picked up to construct a training set which is used to build a QSAR model and then the model is employed to predict the biological activities of the balance compounds. The predicted correlation coefficient and root mean square error are 0.9332 and 0.19, respectively.
