量子化学方法在计算化合物物理、化学、生物学性质中的应用
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摘要
量子化学计算方法是一种非常重要的理论化学方法,在化学信息学中,它属于演绎式的学习方式,即通过求解薛定谔方程直接来计算化合物的性质,它能准确地提供分子结构、性质等方面的相关信息。但是,量子化学方法的应用却受到研究体系的大小及运算时间的限制。定量结构.活性/性质关系是化学信息学中另外一种非常重要的学习方式,即归纳式学习方法。本论文将量子化学方法与定量结构-活性/性质关系研究相结合,发展了一种将演绎式与归纳式学习方式相结合的方法,并将其用于化合物物理、化学、生物性质的理论预测。这种方法建立的模型,不仅具有量子化学精度高的优点,并且具有定量结构-活性/性质关系快速的优势。同时,也促进了化学信息中两大学习方式的互补与交叉,具有很好的应用前景及重要的理论和实际意义。本论文的具体内容共分五章:
第一章简述了化学信息学中两种重要的理论,量子化学理论和定量结构-活性/性质关系(Quantitative Structure-Activity/Property Relationship,QSAR/QSPR),包括它们的基本原理及实现方法。
第二章利用QSPR研究方法,将遗传算法(Genetic Algorithm,GA)和多元线性回归方法(Multiple Linear Regression,MLR)结合,建立了预测苯甲酸、吡啶、喹啉及其它们的取代物等56个化合物药物渗透性的QSPR模型,所选的最终模型包含4个描述符,结果显示,对于训练集R~2=0.94,Q~2=0.91,F=151.36,RMSE=0.22,AARD=10.21%,对测试集的预测结果是R~2=0.92,RMSE=0.26,AARD=13.29%。此外,通过描述符与药物渗透性之间的相关分析,总结出了一些分子结构特征影响药物渗透性的规律,可以用于预测新化合物的渗透性质。
第三章将密度泛函理论应用到QSAR建模过程中,精确预测了52个酚类化合物作用于半胱氨酸天门冬氨酸水解专一型蛋白酶而引起细胞凋亡的活性。首先用DFT方法优化了所研究化合物的结构,并计算了它们的描述符,接着用DUPLEX方法将化合物分为训练集与测试集,然后利用GA方法选出了5个描述符作为多元线性回归方法的建模参数。所建模型经过了严格的内部及外部检验,对于训练集得到的R~2=0.938,测试集得到的R~2=0.939。为了证明这种方法的优越性,我们还采用了半经验的量子化学方法(AM1)来优化所有的分子结构,然后用同样的方法建立模型,结果显不用DFT方法优化分子得到的QSAR模型不仅比半经验的方法得到的模型的预测能力好,还可以得到更多量子化学的描述符。我们将DFT优化结构方法与GA-MLR结合应用到QSAR研究中,不仅克服了以往分子结构不准确给建模过程中带来的误差,还拓宽了QSAR的应用域范围。
第四章主要应用DFT方法研究了含硝基系列化合物的构象,以及Y-NO_2(Y=N,O)单键的键能(bond dissociation energies,BDE)。研究表明对于N-硝基磺胺类和O-硝基醇类这两个系列的化合物,每个分子只有一种稳定的构象,而对于N-硝基酰胺类化合物由于在C-N单键之间存在顺反异构的区别,每个分子有两种稳定的构象,并发现反式构象比顺式构象稳定。计算结果显示适合这三类化合物Y-NO_2键的BDE的理论计算方法不同,分别是:B3P86/6-311++G(d,p)、B3LYP/6-311++G(d,p)、B3LYP/6-311++G(d,p)。最后我们还研究了远程取代基对键离解能的影响,发现Y-NO_2 BDE与σ_p常数呈现负的相关性。本章中得出的这些结论可以应用于计算这三类化合物同系物中未知的Y-NO_2键BDE的计算,从而为研究这三类化合物在生物体内的生物化学反应提供可靠的键能数据。
第五章将量子化学计算与统计学校正方法结合,建立了预测110个过氧化物氧氧单键的BDE的计算方法,此方法是在用一种量子化学方法(密度泛函方法)计算得到的过氧化物氧氧单键的BDE的基础上,通过遗传算法,选出与氧氧单键的BDE相关性较大的5个描述符,并建立了具有校正意义的模型,通过这种方法计算得到的BDE,结果得到了很大的改善,对整个数据集的RMSE由原来的10.88kcal/mol降低到2.42kcal/mol,AARD由原来的9.45%降低到5.66%,总之,所建立的模型可以用于快速的预测其它未知的氧氧单键的BDE。这种将量子化学与统计学校正结合的思路,可以推广到对其它类型单键的BDE理论预测。
Quantum chemistry is an important theory in chemoinformatics,which can,in principle,express all the electroni(?) and geometric properties of molecule accurately. But it was restricted by the studied system and the time of calculation.In this thesis, the quantum chemistry calculation was combined with the quantitative structure-activity /property relationship(QSAR/QSPR),in other words,models combining the two different types of learning methods(deductive and inductive) in chemoinformatics were developed to predict the physico-chemical,biochemical and pharmacological properties of compounds.Using this efficient approach,it can be used to find successful structure-activity/property correlations and then predict the activity or property of other compounds more accurately.At the same time,it can accelerate the proccss for the development of cffective models to design new molecules like drugs,materials.In this thesis,the following studies were carried out:
Chapter 1:A brief description of quantum chemistry and quantitative structure-property/activity relationship(QSAR/QSPR) was introduced,including their basic concept and recent progress.
Chapter 2:A QSPR model was developed for the drug permeability ot 56 compounds,including benzoic acids,pyridines and quinolines.The multiple linear regression(MLR) method was used to build QSPR models based on four descriptors selected by genetic algorithm(GA) using training set samples.Very good result was obtained,for the training set,R~2=0.94,Q~2=0.91,F=151.36,RMSE=0.22, AARD=10.21%.For the test set,the model gave R~2=0.92,RMSE=0.26, AARD=13.29%.By analysis the influence of compounds' structure on drug permeability,we obtained some useful information which would be very useful in the design of potential drugs with desired permeability.
Chapter 3:In this work,an accurate and validated quantitative structure-activity relationship(QSAR) model was developed for the caspase-mediated apoptosis-inducing effect of 52 substituted phenolic compounds in a murine leukemia cell line(L1210).All molecules were respectively optimized by the density functional theory(DFT) and semi-empirical method to obtain the lowest energy conformations. The whole data set was divided into representative training and test sets using DUPLEX method.Then multiple linear regression(MLR) method was used to build QSAR models based on the descriptors selected by genetic algorithm(GA) using training set samples.The built models were rigorously validated both internally and externally.The obtained model based on DFT optimized geometry is better than that based on semi-empirical optimized geometry and the published work with the correlation coefficient(R~2) of 0.938 for the training set and 0.939 for the test set.The result is discussed in the light of the main features that influence the inducing activity of caspase-mediated apoptosis.Density Functional Theory(DFT) is a precise method, which can give the electronic structure of compounds accurately.Combining DFT calculation with QSAR analysis not only overcomes the shortcomings of traditional QSAR effectively,but also expands the traditional scope of application of QSAR.
Chapter 4:Three Density Functional Theory methods(B3LYP,B3PW91 and B3P86) with the 6-31G(d) and 6-311++G(d,p) were used to study the conformation and homolytic Y-NO_2(Y=N,O) bond dissociation energies(BDE) of the three types nitro-containing compounds.It is found that at the site of Y-NO_2 there is only one stable conformation for N-Nitrosulfonamides and O-Nitro alcohols,whereas there are two stable conformations for N-Nitroacylamides and the anti-conformation is favored because of the steric effect.By comparing the computed energies and experimental results,it is noted that different quantum chemical calculational methods are suitable for different molecular systems,B3P86/6-311++G(d,p) provides for N-Nitrosulfonamides,B3LYP/6-311++G(d,p) gives similar BDE with experiment for N-Nitroacylamides and O-Nitro alcohols.Subsequently,the substituent effects on the BDE of the Y-NO_2 bond for three types compounds are further analyzed,the result shows that the electron donating groups are bond-strengthening,whereas electron withdrawing groups are bond-weakening,though for N-Nitrosulfonamides and N-Nitroacylamides,there is a stronger correlation between the substituent electronic effects and the stability of the radical product than that of O-Nitro alcohols.
Chapter 5.Owing to the more BDE values of peroxides which is an important type compounds in troposphere,a fast and relatively method was developed for the prediction BDE of O-O bond of 110 peroxides.By this method,a raw BDE value was obtained from the optimized geometry at DFT,and then an accurate BDE values was obtained by GA procedure.The final model is a five-parameter linear equation and is validated by a leave-one-out cross-validation.Calculated results demonstrated that the QSPR calibration lead to a remarkable reduction of RMSE and AARD:the RMSE is reduced from 10.88kcal/mol to 2.42kcal/mol,the AARD reduced from 9.45%to 5.66%.Comparison of the results by B3LYP/6-31G(d,p) revealed that B3LYP/6-31G(d,p) in combination with a GA calibration is reliable in the accurate prediction of BDE of O-O bond of peroxides.The idea that combining the quantum chemistry calculations and GA calibration would extend to predicting other types BDE in theory methods.
第一章简述了化学信息学中两种重要的理论,量子化学理论和定量结构-活性/性质关系(Quantitative Structure-Activity/Property Relationship,QSAR/QSPR),包括它们的基本原理及实现方法。
第二章利用QSPR研究方法,将遗传算法(Genetic Algorithm,GA)和多元线性回归方法(Multiple Linear Regression,MLR)结合,建立了预测苯甲酸、吡啶、喹啉及其它们的取代物等56个化合物药物渗透性的QSPR模型,所选的最终模型包含4个描述符,结果显示,对于训练集R~2=0.94,Q~2=0.91,F=151.36,RMSE=0.22,AARD=10.21%,对测试集的预测结果是R~2=0.92,RMSE=0.26,AARD=13.29%。此外,通过描述符与药物渗透性之间的相关分析,总结出了一些分子结构特征影响药物渗透性的规律,可以用于预测新化合物的渗透性质。
第三章将密度泛函理论应用到QSAR建模过程中,精确预测了52个酚类化合物作用于半胱氨酸天门冬氨酸水解专一型蛋白酶而引起细胞凋亡的活性。首先用DFT方法优化了所研究化合物的结构,并计算了它们的描述符,接着用DUPLEX方法将化合物分为训练集与测试集,然后利用GA方法选出了5个描述符作为多元线性回归方法的建模参数。所建模型经过了严格的内部及外部检验,对于训练集得到的R~2=0.938,测试集得到的R~2=0.939。为了证明这种方法的优越性,我们还采用了半经验的量子化学方法(AM1)来优化所有的分子结构,然后用同样的方法建立模型,结果显不用DFT方法优化分子得到的QSAR模型不仅比半经验的方法得到的模型的预测能力好,还可以得到更多量子化学的描述符。我们将DFT优化结构方法与GA-MLR结合应用到QSAR研究中,不仅克服了以往分子结构不准确给建模过程中带来的误差,还拓宽了QSAR的应用域范围。
第四章主要应用DFT方法研究了含硝基系列化合物的构象,以及Y-NO_2(Y=N,O)单键的键能(bond dissociation energies,BDE)。研究表明对于N-硝基磺胺类和O-硝基醇类这两个系列的化合物,每个分子只有一种稳定的构象,而对于N-硝基酰胺类化合物由于在C-N单键之间存在顺反异构的区别,每个分子有两种稳定的构象,并发现反式构象比顺式构象稳定。计算结果显示适合这三类化合物Y-NO_2键的BDE的理论计算方法不同,分别是:B3P86/6-311++G(d,p)、B3LYP/6-311++G(d,p)、B3LYP/6-311++G(d,p)。最后我们还研究了远程取代基对键离解能的影响,发现Y-NO_2 BDE与σ_p常数呈现负的相关性。本章中得出的这些结论可以应用于计算这三类化合物同系物中未知的Y-NO_2键BDE的计算,从而为研究这三类化合物在生物体内的生物化学反应提供可靠的键能数据。
第五章将量子化学计算与统计学校正方法结合,建立了预测110个过氧化物氧氧单键的BDE的计算方法,此方法是在用一种量子化学方法(密度泛函方法)计算得到的过氧化物氧氧单键的BDE的基础上,通过遗传算法,选出与氧氧单键的BDE相关性较大的5个描述符,并建立了具有校正意义的模型,通过这种方法计算得到的BDE,结果得到了很大的改善,对整个数据集的RMSE由原来的10.88kcal/mol降低到2.42kcal/mol,AARD由原来的9.45%降低到5.66%,总之,所建立的模型可以用于快速的预测其它未知的氧氧单键的BDE。这种将量子化学与统计学校正结合的思路,可以推广到对其它类型单键的BDE理论预测。
Quantum chemistry is an important theory in chemoinformatics,which can,in principle,express all the electroni(?) and geometric properties of molecule accurately. But it was restricted by the studied system and the time of calculation.In this thesis, the quantum chemistry calculation was combined with the quantitative structure-activity /property relationship(QSAR/QSPR),in other words,models combining the two different types of learning methods(deductive and inductive) in chemoinformatics were developed to predict the physico-chemical,biochemical and pharmacological properties of compounds.Using this efficient approach,it can be used to find successful structure-activity/property correlations and then predict the activity or property of other compounds more accurately.At the same time,it can accelerate the proccss for the development of cffective models to design new molecules like drugs,materials.In this thesis,the following studies were carried out:
Chapter 1:A brief description of quantum chemistry and quantitative structure-property/activity relationship(QSAR/QSPR) was introduced,including their basic concept and recent progress.
Chapter 2:A QSPR model was developed for the drug permeability ot 56 compounds,including benzoic acids,pyridines and quinolines.The multiple linear regression(MLR) method was used to build QSPR models based on four descriptors selected by genetic algorithm(GA) using training set samples.Very good result was obtained,for the training set,R~2=0.94,Q~2=0.91,F=151.36,RMSE=0.22, AARD=10.21%.For the test set,the model gave R~2=0.92,RMSE=0.26, AARD=13.29%.By analysis the influence of compounds' structure on drug permeability,we obtained some useful information which would be very useful in the design of potential drugs with desired permeability.
Chapter 3:In this work,an accurate and validated quantitative structure-activity relationship(QSAR) model was developed for the caspase-mediated apoptosis-inducing effect of 52 substituted phenolic compounds in a murine leukemia cell line(L1210).All molecules were respectively optimized by the density functional theory(DFT) and semi-empirical method to obtain the lowest energy conformations. The whole data set was divided into representative training and test sets using DUPLEX method.Then multiple linear regression(MLR) method was used to build QSAR models based on the descriptors selected by genetic algorithm(GA) using training set samples.The built models were rigorously validated both internally and externally.The obtained model based on DFT optimized geometry is better than that based on semi-empirical optimized geometry and the published work with the correlation coefficient(R~2) of 0.938 for the training set and 0.939 for the test set.The result is discussed in the light of the main features that influence the inducing activity of caspase-mediated apoptosis.Density Functional Theory(DFT) is a precise method, which can give the electronic structure of compounds accurately.Combining DFT calculation with QSAR analysis not only overcomes the shortcomings of traditional QSAR effectively,but also expands the traditional scope of application of QSAR.
Chapter 4:Three Density Functional Theory methods(B3LYP,B3PW91 and B3P86) with the 6-31G(d) and 6-311++G(d,p) were used to study the conformation and homolytic Y-NO_2(Y=N,O) bond dissociation energies(BDE) of the three types nitro-containing compounds.It is found that at the site of Y-NO_2 there is only one stable conformation for N-Nitrosulfonamides and O-Nitro alcohols,whereas there are two stable conformations for N-Nitroacylamides and the anti-conformation is favored because of the steric effect.By comparing the computed energies and experimental results,it is noted that different quantum chemical calculational methods are suitable for different molecular systems,B3P86/6-311++G(d,p) provides for N-Nitrosulfonamides,B3LYP/6-311++G(d,p) gives similar BDE with experiment for N-Nitroacylamides and O-Nitro alcohols.Subsequently,the substituent effects on the BDE of the Y-NO_2 bond for three types compounds are further analyzed,the result shows that the electron donating groups are bond-strengthening,whereas electron withdrawing groups are bond-weakening,though for N-Nitrosulfonamides and N-Nitroacylamides,there is a stronger correlation between the substituent electronic effects and the stability of the radical product than that of O-Nitro alcohols.
Chapter 5.Owing to the more BDE values of peroxides which is an important type compounds in troposphere,a fast and relatively method was developed for the prediction BDE of O-O bond of 110 peroxides.By this method,a raw BDE value was obtained from the optimized geometry at DFT,and then an accurate BDE values was obtained by GA procedure.The final model is a five-parameter linear equation and is validated by a leave-one-out cross-validation.Calculated results demonstrated that the QSPR calibration lead to a remarkable reduction of RMSE and AARD:the RMSE is reduced from 10.88kcal/mol to 2.42kcal/mol,the AARD reduced from 9.45%to 5.66%.Comparison of the results by B3LYP/6-31G(d,p) revealed that B3LYP/6-31G(d,p) in combination with a GA calibration is reliable in the accurate prediction of BDE of O-O bond of peroxides.The idea that combining the quantum chemistry calculations and GA calibration would extend to predicting other types BDE in theory methods.
引文
[1]J.Gasteiger,T.Engel,Chemoinformatics,Wiley-VCH,2003.
[2]邵学广,蔡文生,《化学信息学》,科学出版社,2005.
[3]缪强,《化学信息学导论》,高等教育出版社,2001.
[4]徐光宪,黎乐民,《量子化学-基本原理和从头计算法》,科学出版社,1985.
[5]C.J.Cramer,Essentials of Computational Chemistry,John WiLey&Sons,New York,2002.
[6]C.K.Majumdar,K.Walter,Nobel Prize in Chemistry in 1998,Current Science 1999,76,1451-1453.
[7]陈凯先,蒋华良,汝运,《计算机辅助药物设计-原理、方法及应用》,上海科技出版社,2000.
[8]陈志行,《有机分子轨道理论》,山东科技出版社,1991.
[9]陈念贻等,《计算化学及其应用》,上海科技出版社,1986.
[10]张德聪,《结构化学》,华南理工大学出版社,2000.
[11]A.Frisch,M.J.Frisch,G.W.Trucks,Gaussian 98 User's Reference,Gaussian.Inc.1998.
[12]W.J.Hehre,R.F.Stewart,J.A.Pople,Self-consistent molecular-orbital methods.I.Use of gaussian expansions of Slater-type atomic orbitals.J.Chem.Phys.1969,51,2657-2664.
[13]J.B.Collins,P.V.R.Schleyer,J.S.Binkley,and J.A.Pople,Self-consistent molecular orbital methods.ⅩⅦ.Geometries and binding energies of second-row molecules.A comparison of three basis sets.J.Chem.Phys.1976,64,5142-5151.
[14]J.S.Binkley,J.A.Pople,W.J.Hehre,Self-consistent molecular orbital methods.21.Small split-valence basis sets for first-row elements.J.Am.Chem.Soc.1980,102,939-974.
[15]M.S.Gordon,J.S.Binkley,J.A.Pople,W.J.Pietro,W.J.Hehre,Self-consistent molecular-orbital methods.22.Small split-valence basis sets for second-row elements.J.Am.Chem.Soc.1982,104,2797-2803.
[16]W.J.Pietro,M.M.Francl,W.J.Hehre,D.J.Defrees,J.A.Pople,J.S.Binkley,Self-consistent molecular orbital methods.24.Supplemented small split-valence basis sets for second-row elements.J.Am.Chem.Soc.1982,104,5039-5048.
[17]K.D.Dobbs,W.J.Hehre,Molecular orbital theory of the properties of inorganic and organcmetallic compounds.4.Extended basis sets for third- and fourth-row,main-group elements.J.Comp.Chem.1986,7,359-378.
[18]K.D.Dobbs,W.J.Hehre,Molecular orbital theory of the properties of inorganic and organometallic compounds.5.Extended basis sets for first-row transition metals.J.Comp.Chem.1987,8,861-879.
[19]K.D.Dobbs,W.J.Hehre,Molecular orbital theory of the properties of inorganic and organometallic compounds.6.Extended basis sets for second-row transition metals.J.Comp.Chem.1987,8,880-893.
[20]R.Ditchfield,W.J.Hehre,J.A.Pople,Self-consistent molecular-orbital methods.Ⅺ.An extended Gaussian-type basis for molecular-orbital studies of organic molecules.J.Chem.Phys.1971,54,724-728.
[21]W.J.Hehre,R.Ditchfield,J.A.Pople,Self-consistent molecular orbital methods.Ⅻ.Further extensions of Gaussian-type basis sets for use in molecular orbital studies of organic molecules.J.Chem.Phys.1972,56,2257-2261.
[22]P.C.Hariharan,J.A.Pople,Accuracy of AHn equilibrium geometries by single determinant molecular orbital theory.Mol.Phys.1974,27,209-214.
[23]M.S.Gordon,The isomers of silacyclopropane.Chem.Phys.Lett.1980,76,163-168.
[24]P.C.Hariharan,J.A.Pople,The influence of polarization functions on molecular orbital hydrogenation energies.Theo.Chim.Acta 1973,28,213-222.
[25]J.P.Blaudeau,M.P.McGrath,L.A.Curtiss,L.Radom,Extension of Gaussian-2(G2) theory to molecules containing third-row atoms K and Ca.J.Chem.Phys.1997,107,5016-5021.
[26]M.M.Francl,W.J.Pietro,W.J.Hehre,J.S.Binkley,D.J.DeFrees,J.A.Pople,M.S.Gordon,Self-consistent molecular orbital methods.ⅩⅩⅢ.A polarization-type basis set for second-row elements.J.Chem.Phys.1982,77,3654-3665.
[27]R.C.Binning,Jr.,L.A.Curtiss,Compact contracted basis sets for third-row atoms:Gallium-krypton.J.Comp.Chem.1990,11,1206-1216.
[28]V.A.Rassolov,J.A.Pople,M.A.Ratner,T.L.Windus,6-31G~* basis set for atoms K through Zn.J.Chem.Phys.1998,109,1223-1229.
[29]V.A.Rassolov,M.A.Ratner,J.A.Pople,P.C.Redfern,L.A.Curtiss,6-31G~*basis set for third-row atoms.J.Comp.Chem.2001,22,976-984.
[30]T.H.Dunning,Jr.,P.J.Hay,in Modern Theoretical Chemistry,Plenum Press,New York,1976.
[31]G.A.Petersson,A.Bennett,T.G.Tensfeldt,M.A.AI-Laham,W.A.Shirley,J.Mantzaris,A complete basis set model chemistry.Ⅰ.The total energies of closed-shell atoms and hydrides of the first-row atoms.J.Chem.Phys.1988,89,2193-2218.
[32]G.A.Petersson,M.A.AI-Laham,A complete basis set model chemistry.Ⅱ.Open-shell systems and the total energies of the fist-row atoms.J.Chem.Phys.1991,94,6081-6090.
[33]K.Raghavachari,G.W.Trucks,Highly correlated systems.Excitation energies of first row transition metals Sc-Cu.J.Chem.Phys.1989,91,1062-1065.
[34]K.Raghavachari,J.A.Pople,E.S.Replogle,M.Head-Gordon,Fifth-order moller-plesset perturbation theory:comparison of existing correlation methods and implementation of new methods correct to fifth-order.J.Chem.Phys.1990,94,5579-5586.
[35]K.Raghavachari,J.A.Pople,E.S.Replogle,M.Head-Gordon,N.C.Handy,Size-consistent brueckner theory limited to double and triple substitutions.Chem.Phys.Lett.1990,167,115-121.
[36]T.Clark,J.Chandrasekhar,G.W.Spitznagel,P.R.Schleyer,Efficient diffuse function-augmented basis sets for anion calculations.Ⅲ.The 3-21G basis set for first-row elements,lithium to fluorine.J.Chem.Phys.1983,4,294-301.
[37]M.J.Frich,J.A.Pople,J.S.Binkley,Self-consistent molecular orbital methods.25.Supplementary functions for Gaussian basis sets.J.Chem.Phys.1984,80,3265-3269.
[38]W.Stevens,H.Basch,J.Krauss,Compact effective potentials and efficient shared-exponent basis sets for the first-and second-row atoms.J.Chem.Phys.1984,81,6026-6033.
[39]W.J.Stevens,M.Krauss,Ⅱ.Basch,P.G.Jasien,Relativistic compact effective potentials and efficient,shared-exponent basis sets for the third-,fourth-,and fifth-row atoms.Can.J.Chem.1992,70,612-630.
[40]T.R.Cundari,W.J.Stevens,Effective core potential methods for the lanthanides.J.Chem.Phys.1993,98,5555-5565.
[41]P.J.Hay,W.R.Wadt,Ab initio effective core potentials for molecular calculations for the transition metal atoms Sc to Hg.J.Chem.Phys.1985,82,270-283.
[42]W.R.Wadt,P.J.Hay,Ab initio effective core potentials for molecular calculations,potentials for main group elements Na to Bi.J.Chem.Phys.1985,82,284-298.
[43]P.J.Hay,W.R.Wadt,Ab initio effective core potentials for molecular calculations.Potentials for K to Au including the outermost core orbitals.J.Chem.Phys.1985,82,299-310.
[44]D.E.Woon,T.H.Dunning,Jr.,Gaussian basis sets for use in correlated molecular calculations.Ⅲ.The second-row atoms,Al-Ar.J.Chem.Phys.1993,98,1358-1371.
[45]R.A.Kendall,T.H.Dunning,Jr.,R.J.Harrison,Electron affinities of the first-row atoms revisited.Systematic basis sets and wave functions.J.Chem.Phys.1992,96,6796-6806.
[46]T.H.Dunning,Jr.,Gaussian basis sets for use in correlated molecular calculations.I.The atoms boron through neon and hydrogen.J.Chem.Phys.1989,90,1007-1023.
[47]K.A.Peterson,D.E.Woon,T.H.Dunning,Jr.,Benchmark calculations with correlated molecular wave functions.IV.The classical barrier height of the H + H_2 →H_2 + H reaction.J.Chem.Phys.1994,100,7410-7415.
[48]A.K.Wilson,T.van Mourik,T.H.Dunning,Jr.,Gaussian basis sets for use in correlated molecular calculations.VI.Sextuple zeta correlation consistent basis sets for boron through neon.J.Mol.Struct.(Theochem) 1997,388,339-349.
[49]E.R.Davidson,Comment on “Comment on Dunning's correlation-consistent basis sets” Chem.Phys.Lett.1996,260,514-518.
[50]A.R.Leach,Molecular Modeling,Addison Wesley Long-man Limited,1996.
[51]R.Hoffmann,An extended H(u|¨)ckel theory.I.Hydrocarbons.J.Chem.Phys.1963,39,1397-1412.
[52]J.A.Pople,D.P.Santry,G.A.Segal,Approximate self-consistent molecular orbital theory .I.Invariant procedures.J.Chem.Phys.1965,43,S129-S135.
[53]J.A.Pople,G.A.Segal,Approximate self-consistent molecular orbital theory.Ⅱ.Calculation with complete neglect of different overlap.J.Chem.Phys.1965,43,S136-S151.
[54]J.A.Pople,G.A.Segal,Approximate self-consistent molecular orbital theory Ⅲ.CNDO results for AB2 and AB3 systems.J.Chem.Phys.1966,44,3289-3296.
[55]J.A.Pople,D.L.Beveridge,P.A.Dobosh,Approximate self-consistent molecular orbital theory V.Intermediate neglect of differential overlap.J.Chem.Phys.1967,47,2026-2033.
[56]M.J.S.Dewar,E.Haselbach,Ground states of σ-bonded molecules.Ⅸ.The MINDO/2 method.J.Am.Chem.Soc.1970,92,590-598.
[57]R.C.Bingham,M.J.S.Dewar,D.H.Lo,Ground states of molecules.J.Am. Chem.Soc.1975,97,1289-1293.
[58]M.J.S.Dewar,Ground states of molecules.38.The MNDO Method.Approximations and Parameters.J.Am.Chem.Soc.1977,99,4899-4907.
[59]M.J.S.Dewar,E.G.Zoebisch,E.F.Healy,J.J.P.Stewart,AMI:A new general purpose quantum mechanical molecular model.J.Am.Chem.Soc.1985,107,3902-3909.
[60]J.J.P.Stewart,Optimization of parameters for semiempirical methods Ⅰ.Method.J.Comp.Chem.1989,10,209-220.
[61]J.J.P.Stewart,Optimization of parameters for semiempirical methods Ⅱ.Applications.J.Comp.Chem.1989,10,221-264.
[62]J.J.P.Stewart,Steawrt Computational Chemistry,2007,http://OpenMOPAC.net.
[63]J.J.P.Stewart,Optimization of parameters for semiempirical methods V:modification of NDDO approximations and application to 70 Elements.J.Mol.Model 2007,13,1173-1213.
[64]R.G.Parr,W.Yang,Density Functional Theory of Atoms and molecules,Oxford University Press,New York,1989.
[65]P.Hohenberg,W.Kohn,Inhomogeneous electron gas.Phys.Rev.1964,136,B864-B871.
[66]W.Kohn,L.J.Sham,Self-consistent equations including exchange and correlation effects.Phys.Rev.1965,140,A1133-A1138.
[67]J.A.Pople,P.M.W.Gill,B.G.Johnson,Kohn-Sham density-functional theory within a finite basis set.Chem.Phys.Lett.1992,199,557-560.
[68]A.D.Becke,Density-functional thermochemistry.Ⅲ.The role of exact exchange.J.Chem.Phys.1993,98,5648-5652.
[69]傅尧,中国科学技术大学博士学位论文,2005.
[70]丁迅雷,中国科学技术大学博士学位论文,2004.
[71]许禄,胡昌玉,《应用化学图论》,北京科学出版社,2000.
[72]王连生,韩朔睽,《分子结构性质与活性》,北京化学工业出版社,1997.
[73]刘焕香,兰州大学博士学位论文,2005.
[74]http://www.nisc.com/cis
[75]http://www.epa.gov/srs
[76]http://www.ccdc.cam.ac.uk
[77]http://ulisse.etoit.eudra.org/Ecdin/Ecdin.html
[78]http://www.bid.med.jhmi.edu/Dan/proteins/pir-last.html
[79]http://www.boc.chem.uu.nl/sugabase/datases.html
[80]http://www.rcsb.org/pdb/Welcome.do
[81]http://www.pubs.acs.org
[82]http://sciencedirect.com
[83]http://www3.interscience.wiley.com/cgi-bin/home
[84]http://www.springerlink.com
[85]http://www.cnki.net/index.htm
[86]http://wanfang.calis.edu.cn/wfkixx/cacp.html
[87]http://www.tydata.com
[88]任月英,兰州大学博士学位论文,2007.
[89]R.W.Kennard,L.A.Stone,Computer aided design of experiments.Technometrics,1969,11,137-148.
[90]R.D.Snee,Validation of regression models:methods and examples.Technometrics,1977,19,415-428.
[91]A.R.Katritzky,V.S.Lobanov,M.Karelson,CODESSA:Reference Manual;Version 2,University of Florida,1994.
[92]D.Rogers,A.J.Hopfinger,Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships.J.Chem.Inf Comput.Sci.1994,34,854-866.
[93]H.Kubinyi,Variable selection in QSAR studies.I.An evolutionary Algorithm.Quant.Struct.-Act.Rel.1994,13,285-294.
[94]J.G.Topliss,R.J.Costello,Chance correlations in structure-activity studies using multiple regression analysis.J.Med.Chem.,1972,15,1066-1068.
[95]王惠文,《偏最小二乘回归方法及其应用[M》,北京国防工业出版社,1999.
[96]姚小军,兰州大学博士学位论文,2005.
[97]R.Wehrens,H.Putter,L.M.C.Buydens,The bootstrap:A tutorial.Chemom.Int. Lab.Syst.2000,54,35-52.
[98]R.Guha,J.R.Serra,P.C.Jurs,Generation of QSAR sets with a self-organizing map.J.Mol.Graph.Model.2004,23,1-14.
[1]W.J.Egan,G.Lauri,Prediction of intestinal permeability.Adv.Drug Delivery Rev. 2002,54,273-289.
[2]M.D.Wessel,P.C.Jurs,J.W.Tolan,S.M.Muskal,Prediction of human intestinal absorption of drug compounds from molecular structure.J.Chem.Inf.Comput.Sci.1998,38,726-735.
[3]T.Hou,J.Wang,W.Zhang,W.Wang,X.Xu,Recent advances in computational prediction of drug absorption and permeability in drug discovery.Curr.Med.Chem.2006,13,2653-2667.
[4]W.P.Walters,M.A.Murcko,Prediction of 'drug-likeness'.Adv.Drug Delivery Rev.2002,54,255-271.
[5]C.Acharya,P.R.Seo,J.E.Polli,A.D.MacKerell,Computational model for predicting chemical substituent effects on passive drug permeability across parallel artificial membranes.Mol.Pharmaceutics 2008,5,818-828.
[6]A.Walter,J.Gutknecht,Permeability of small nonelectrolytes through lipid bilayer membranes.J.Membr.Biol.1986,90,207-217.
[7]I.J.Chen,R.Taneja,D.Yin,P.R.Seo,D.Young,A.D.MacKerell,Jr.,J.E.Polli,Chemical substituent effect on pyridine permeability and mechanistic insight from computational molecular descriptors.Mol.Pharmaceutics 2006,3,745-755.
[8]F.Barbosa,D.Horvath,Molecular similarity and property similarity.Curr.Top.Med.Chem.2004,4,589-600.
[9]A.R.Leach,M.M.Hann,The in silico world of virtual libraries.Drug Discovery Today 2000,5,326-336.
[10]P.Stenberg, U.Norinder, K.Luthman,P.Artursson, Experimental and computational screening models for the prediction of intestinal drug absorption.J.Med.Chem.2001,44,1927-1937.
[11]G.Subramanian,D.B.Kitchen,Computational approaches for modeling human intestinal absorption and permeability.J.Mol.Model.2006,12,577-589.
[12]HyperChem,Release 6.0 for Windows,Hypercube,Inc.,2000.
[13]T.Srl,Dragon for Windows (Software for Molecular Descriptors Calculations)Version 5.4,2006.
[14]R.Todeschini,V.Consonni,Handbook of Molecular Descriptors,Wiley-VCH, Weinheim,Germany,2000.
[1]J.F.Kerr,A.H.Wyllie,A.R.Currie,Apoptosis:a basic biological phenomenon with wide-ranging implications in tissue kinetics.Br.J.Cancer 1972,26,239-257.
[2]H.Steller,Mechanisms and genes of cellular suicide.Science 1995,267,1445-1449.
[3]S.Kothakota,T.Azuma,C.Reinhard,A.Klipel,J.Tang,K.Chu,T.McGarry,M.Kirschner,K.Koths,D.Kwiatkowski,L.Williams,Caspase-3-generated fragment of gelsolin:effector of morphological change in apoptosis.Science 1997,278,294-298.
[4]G.S.Salvesen,V.M.Dixit,Caspases:intracellular signaling by proteolysis.Cell 1997,91,443-446.
[5]P.Villa,S.H.Kaufrnann,W.C.Earnshaw,Caspases and caspase inhibitors.Treds.Biochem.Sci.1997,22,388-393.
[6]L.Herr,K.M.Debatin,Cellular stress response and apoptosis in cancer therapy.Blood 2001,98,2603-2614.
[7]T.Rich,R.L.Allen,A.H.Wyllie,Defying death after DNA damage.Nature 2000,407,777-783.
[8]H.F.Stich,The beneficial and hazardous effects of simple phenolic compounds.Mutat.Res.1991,259,307-324.
[9]C.Hansch,B.Bonavida,A.R.Jazirehi,J.J.Cohen,C.Milliron,A.Kurup,Quantitative structure-activity relationships of phenolic compounds causing apoptosis.Bioorg.Med.Chem.2003,11,617-620.
[10]C.Hansch,A.Jazirehi,S.B.Mekapati,R.Garg,B.Bonavidab,QSAR of apoptosis induction in various cancer cells.Bioorg.Med.Chem.2003,11,3015-3019.
[11]C.D.Selassie,S.Kapur,R.P.Verma,M.Rosario,Cellular apoptosis and cytotoxicity of phenolic compounds:a quantitative structure-activity relationship study.J.Med.Chem.2005,48,7234-7242.
[12]E.Eroglu,H.Turkmen,A DFT-based quantum theoretic QSAR study of aromatic and heterocyclic sulfonamides as carbonic anhydrase inhibitors against isozyme,CA-Ⅱ.J.Mol.Graphics Modell 2007,26,701-708.
[13]J.Wan,L.Zhang,G.F.Yang,Quantitative structure-activity relationships for phenyl triazolinones of protoporphyrinogen oxidase inhibitors:A density functional theory study.J.Comput.Chem.2004,25,1827-1832.
[14]Z.Xi,Z.H.Yu,C.W.Niu,S.R.Ban,G.F.Yang,Development of a general quantumchemical descriptor for steric effects:density functional theory based QSAR study of herbicidal sulfonylurea analogues.J.Comput.Chem.2006,27,1571-1576.
[15]R.G.Parr,W.Yang,Density Functional Theory of Atoms and Molecules,Oxford University Press,Oxfoed,1989.
[16]A.D.Becke,A new mixing of Hartree-Fock and local density-functional theories.J.Chem.Phys.1993,98,1372-1377.
[17]A.D.Becke,Density-functional thermochemistry,Ⅲ.The role of exact exchange.J.Chem.Phys.1993,98,5648-5652.
[18]G.A.Petersson,A.Bennett,T.G.Tensfeldt,M.A.Al-Laham,W.A.Shirley,J.Mantzaris,A complete basis set model chemistry.Ⅰ.The total energies of closed-shell atoms and hydrides of the first-row atoms.J.Chem.Phys.1988,89,2193-2218.
[19]M.J.Frisch,G.W.Trucks,H.B.Schlegel,G.E.Scuseria,M.A.Robb,J.R. Cheeseman,V.G.Zakrzewski,J.A.Montgomery,Jr.,R.E.Stratmann,J.C.Burant,S.Dapprich,J.M.Millam,A.D.Daniels,K.N.Kudin,M.C.Strain,O.Farkas,J.Tomasi,V.Barone,M.Cossi,R.Cammi,B.Mennucci,C.Pomelli,C.Adamo,S.Clifford,J.Ochterski,G.A.Petersson,P.Y.Ayala,Q.Cui,K.Morokuma,D.K.Malick,A.D.Rabuck,K.Raghavachari,J.B.Foresman,J.Cioslowski,J.A.Ortiz,A.G.Baboul,B.B.Stefanov,G Liu,A.Liashenko,P.Piskorz,I.Komaromi,R.Gomperts,R.L.Martin,D.J.Fox,T.Keith,M.A.Al-Laham,C.Y.Peng,A.Nanayakkara,C.Gonzalez,M.Challacombe,P.M.W.Gill,B.Johnson,W.Chen,M.W.Wong,J.L.Andres,C.Gonzalez,M.Head-Gordon,E.S.Replogle,J.A.Pople,Gaussian 98,Revision A.9.Gaussian,Inc.,Pittsburgh,PA 1998.
[20]A.R.Katritzky,V.S.Lobanov,M.Karelson,CODESSA:Training Manual,University of Florida,Gainesville,FL1995.
[21]B.Hemmateenejad,M.A.Safarpour,R.Miri,F.Taghavi,Application of ab initio theory for the QSAR study of 1,4-dihydropyridine-based calcium channel antagonist.J.Comput.Chem.2004,25,1495-1503.
[22]J.Lameira,C.N.Alves,V.Moliner,E.Silla,A density functional study of flavonoid compounds with anti-HIV activity.Eur.J.Med.Chem.2006,41,616-623.
[23]A.B.Sannigrahi,Ab initio Molecular Orbital Calculations of Bond Index and Valency.Adv.Quant.Chem.1992,23,301-351.
[24]R.D.Snee, Validation of regression models: methods and examples.Technometrics 1977,19,415-428.
[25]Y.Y.Ren,H.X.Liu,X.J.Yao,M.C.Liu,Prediction of ozone tropospheric degradation rate constants by projection pursuit regression.Anal.Chim.Acta.2007,589,150-158.
[26]B.Hemmateenejad,R.Miri,M.Akhond,M.Shamsipur,QSAR study of the calcium channel antagonist activity of some recently synthesized dihydropyridine derivatives.An application of genetic algorithm for variable selection in MLR and PLS methods.Chemometr.Intell.Lab.Syst.2002,64,91-99.
[27]O.Deeb,B.Hemmateenejad,A.Jaber,R.G.Juarez,R.Miri,Effect of the electronic and physicochemical parameters on the carcinogenesis activity of some sulfa drugs using QSAR analysis based on genetic-MLR and genetic-PLS.Chemosphere 2007,67,2122-2130.
[28]J.Caballero,L.Fernandez,J.I.Abreu,M.Fernandez,Amino Acid Sequence Autocorrelation vectors and ensembles of Bayesian-Regularized Genetic Neural Networks for prediction of conformational stability of human lysozyme mutants.J.Chem.Inf.Model.2006,46,1255-1268.
[29]M.Fernandez,J.Caballero,Bayesian-regularized genetic neural networks applied to the modelling of non-peptide antagonists for the human luteinizing hormone-releasing hormone receptor.J.Mol.Graph.Model.2006,25,410-422.
[30]L.Fernandez,J.Caballero,J.I.Abreu,M.Fernandez,Amino acid sequence autocorrelation vectors and Bayesian-regularized genetic neural networks for modeling protein conformational stability:gene v protein mutants.Proteins 2007,67,834-852.
[31]R.Todeschini,MobyDigs-software for Multilinear Regression Analysis and Variable Subset Selection by Genetic Algorithm,Talete srl,Milan,Italy,2002.
[32]R.Leardi,R.Boggia,M.Terrile,Genetic algorithms as a strategy for feature selection.J.Chemom.1992,6,267-281.
[33]R.Todeschini,A.Maiocchi,V.Consonni,The K correlation index:theory development and its application in chemometrics.Chemom.Intell.Lab.Syst.1999,46,13-29.
[34]A.J.Miller,Subset Selection in Regression,Chapman & Hall,London,UK 1990.
[35]A.C.Atkinson,Plots,Transformations and Regression,Oxford University Press,Oxford 1985.
[36]H.X.Liu,E.Papa,P.Gramatica,Evaluation and QSAR modeling on multiple endpoints of estrogen activity based on different bioassays.Chemosphere 2008,70,1889-1897.
[37]S.C.Basak,A.T.Balaban,G.D.Grunwald,B.D.Gute,Topological indices:Their nature and mutual relatedness.J.Chem.Inf.Comput.Sci.2000,40, 891-898.
[38]A.R.Katritzky,D.B.Tatham,U.Maran,Theoretical descriptors for the correlation of aquatic toxicity of environmental pollutants by quantitative structure-toxicity relationships.J.Chem.Inf.Comput.Sci.2001,41,1162-1172.
[39]R.C.Weast,Handbook of Chemistry and Physics,CRC Press,Cleveland,1974.
[40]D.T.Stanton,L.M.Egolf,P.C.Jurs,M.G.Hicks,Computer-assisted prediction of normal boiling points of pyrans and pyrroles.J.Chem.Inf.Comput.Sci.1992,32,306-316.
[41]D.T.Stanton,P.C.Jurs,Development and use of charged partial surface area structural descriptors in computer assissted quantitative structure property relationship studies.Anal.Chem.1990,62,2323-2329.
[42]H.Van der Voet,Comparing the predictive accuracy of models using a simple randomization test.Chemom.Intell.Lab.Syst.1994,25,313-323.
[1]S.Pfeiffer,B.Mayer,B.Hemmens,Nitric Oxide:Chemical Puzzles Posed by a Biological Messenger.Angew.Chem.Int.Ed.1999,38,1714-1731.
[2]T.S.Kurtikyan,P.C.Ford,Reactions of nitrogen oxides with heme models:spectral characterization of an elusive five-coordinate Fe~Ⅲ(porphyrin) nitrito intermediate.Angew.Chem.Int.Ed.2006,45,492-496.
[3]T.S.Kurtikyan,A.A.Hovhannisyan,M.E.Hakobyan,J.C.Patterson,A.Iretskii,P.C.Ford,Reactions of nitrogen oxides with the five-coordinate Fe~Ⅲ(porphyrin)nitrito intermediate Fe(Por)(ONO) in sublimed solids.J.Am.Chem.Soc.2007,129,3576-3585.
[4]M.Kirsch,H.-G.Korth,R.Sustmann,H.de Groot,The pathobiochemistry of nitrogen dioxide.Biol.Chem.2002,383,389-399.
[5]S.Pfeiffer,A.Lass,K.Schmidt,B.Mayer,Protein tyrosine nitration in mouse peritoneal macrophages activated in vitro and in vivo:evidence against an essential role of peroxynitrite.FASEBJ.2001,75,2355-2364.
[6]M.G.Espey,S.Xavier,D.D.Thomas,K.M.Miranda,D.A.Wink,Direct real-time evaluation of nitration with green fluorescent protein in solution and within human cells reveals the impact of nitrogen dioxide vs.peroxynitrite mechanisms.Proc.Natl.Acad.Sci.U.S.A.2002,99,3481-3486.
[7]X.Liu,M.J.S.Miller,M.S.Joshi,D.D.Thomas,J.R.Lancaster,Accelerated reaction of nitric oxide with O_2 within the hydrophobic interior of biological membranes.Proc.Natl.Acad.Sci.U.S.A.1998,95,2175-2179.
[8]T.S.Kurtikyan,G.M.Gulyan,G.G.Martirosyan,M.D.Lim,P.C.Ford,Reactions of nitrogen oxides with heme models.Spectral and kinetic study of nitric oxide reactions with solid and solute Fe~Ⅲ(TPP) (NO_3).J.Am.Chem.Soc.2005,127,6216-6224.
[9]X.Li,X.Q.Zhu,F.Zhang,X.X.Wang,J.P.Cheng,Establishment of heterolytic and homolytic Y-NO_2 bond dissociation energy scales of nitro-containing compounds in acetonitrile:chemical origin of NO_2 release and capture.J.Org.Chem.2008,73,2428-2431.
[10]R.Bosque,J.J.Sales,A QSPR study of O-H bond dissociation energy in phenols.Chem.Inf.Comput.Sci.2003,43,637-642.
[11]C.Z.Cao,Y.B.Lin,Evaluation of bond dissociation energy for carbon-hydrogen bond in alkane and its application.Chin.J.Org.Chem.2003,23,207-211.
[12]Y.Fu,L.Liu,B.L.Lin,Y.Mou,Y.H.Cheng,Q.X.Guo,Remote substituent effects on homolytic bond dissociation energies.J.Org.Chem.2003, 68,4657-4662.
[13]P.C.Nam,M.T.Nguyen,A.K.Chandra,Theoretical study of the substituent effects on the S-H bond dissociation energy and ionization energy of 3-pyridinethiol:Prediction of novel antioxidant.J.Phys.Chem.A 2006,110,10904-10911.
[14]F.Agapito,P.M.Nunes,B.J.C.Cabral,R.M.B.d.Santos,J.A.M.Sim(?)es, Energetics of the allyl group.J.Org.Chem.2007,72,8770-8779.
[15]J.X.Shao,X.L.Cheng,X.D.Yang,Calculations of the bond dissociation energies for NO_2 scission in some nitro compounds.Struct.Chem.2005,16,457-460.
[16]J.X.Shao,X.L.Cheng,X.D.Yang,The C-NO_2 bond dissociation energies of some nitroaromatic compounds:DFT study.Struct.Chem.2006,17,547-550.
[17]J.X.Shao,X.L.Cheng,X.D.Yang,Density functional calculations of bond dissociation energies for removal of the nitrogen dioxide moiety in some nitroaromatic molecules.J.Mol.Struct.(Theochem) 2005,755,127-130.
[18]H.J.Chen,X.L.Cheng,Z.G.Ma,X.F.Su,Theoretical studies of C-NO_2 bond dissociation energies for chain nitro compounds.J.Mol.Struct.(Theochem) 2007,807,43-47.
[19]M.J.Frisch,G.W.Trucks,H.B.Schlegel,G.E.Scuseria,M.A.Robb,J.R.Cheeseman,V.G Zakrzewski,J.A.Montgomery,Jr.,R.E.Stratmann,J.C.Burant,S.Dapprich,J.M.Millam,A.D.Daniels,K.N.Kudin,M.C.Strain,O.Farkas,J.Tomasi,V.Barone,M.Cossi,R.Cammi,B.Mennucci,C.Pomelli,C.Adamo,S.Clifford,J.Ochterski,G.A.Petersson,P.Y.Ayala,Q.Cui,K.Morokuma,D.K.Malick,A.D.Rabuck,K.Raghavachari J.B.Foresman,J.Cioslowski,J.A.Ortiz,A.G.Baboul,B.B.Stefanov,G.Liu,A.Liashenko,P.Piskorz,I.Komaromi,R.Gomperts,R.L.Martin,D.J.Fox,T.Keith,M.A.Al-Laham,C.Y.Peng,A.Nanayakkara,C.Gonzalez,M.Challacombe,P.M.W.Gill,B.Johnson,W.Chen,M.W.Wong,J.L.Andres,C.Gonzalez,M.Head-Gordon,E.S.Replogle,J.A.Pople,Gaussian 98,Revision A.9.Gaussian,Inc.,Pittsburgh,PA 1998.
[20]Y.Y.Ren,H.X.Liu,X.J.Yao,M.C.Liu,Prediction of ozone tropospheric degradation rate constants by projection pursuit regression.Anal.Chim.Acta 2007,589,150-158.
[1]I.M.Konen,I.B.Pollack,E.X.J.Li,M.E.Vamer,J.F.Stanton,Infrared overtone spectroscopy and unimolecular decay dynamics of peroxynitrous acid.J.Chem.Phys.2005,122,094320/1-094320/16.
[2]P.C.Do Couto,B.J.C.Cabral,J.A.M.Sim(?)es,S-H bond dissociation enthalpies:The importance of a complete basis set approach.Chem.Phys.Lett.2006,421,504-507.
[3]P.C.Nam,M.T.Nguyen,A.K.Chandra,Effect of substituents on the P-H bond dissociation enthalpies of phenylphosphines and proton affinities of phenylphosphine anions:A DFT study.J.Phys.Chem.A 2004,108,11362-11368.
[4]Y.M.Wang,Y.Fu,L.Liu,Q.X.Guo,Substituent effects on the ring opening of 2-aziridinylmethyl radicals.J.Org.Chem.2005,70,3633-3640.
[5]F.Agapito,P.M.Nunes,B.J.C.Cabral,R.M.B.d.Santos,J.A.M.SimOes,Energetics of the allyl group.J.Org.Chem.2007,72,8770-8779.
[6]M.J.Li,L.Liu,Y.Fu,Q.X.Guo,Development of an ONIOM-G3B3 method to accurately predict C-H and N-H bond dissociation enthalpies of ribonucleosides and deoxyribonucleosides.7.Phys.Chem.5 2005,109,13818-13826.
[7]Y.Feng,L.Liu,J.T.Wang,H.Huang,Q.X.Guo,Assessment of experimental bond dissociation energies using composite ab Initio methods and evaluation of the performances of density functional methods in the calculation of bond dissociation energies.J.Chem.Inf.Comput.Sci.2003,43,2005-2013.
[8]D.S.Gabriel,W.B.Joseph,Thermochemistry,bond Energies,and internal rotor potentials of dimethyl tetraoxide.J.Phys.Chem.A 2007,111,12026-12036.
[10]Y.R.Luo,Comprehensive Handbook of Chemical Bond Energies,CRC Press:London,U.K.,2007.
[11]M.J.Frisch,G.W.Trucks,H.B.Schlegel,G E.Scuseria,M.A.Robb,J.R.Cheeseman,V.G.Zakrzewski,J.A.Montgomery,Jr.,R.E.Stratmann,J.C.Burant,S.Dapprich,J.M.Millam,A.D.Daniels,K.N.Kudin,M.C.Strain,O.Farkas,J.Tomasi,V.Barone,M.Cossi,R.Cammi,B.Mennucci,C.Pomelli,C.Adamo,S.Clifford,J.Ochterski,G.A.Petersson,P.Y.Ayala,Q.Cui,K.Morokuma,D.K.Malick,A.D.Rabuck,K.Raghavachari,J.B.Foresman,J.Cioslowski,J.A.Ortiz,A.G.Baboul,B.B.Stefanov,G Liu,A.Liashenko,P.Piskorz,I.Komaromi,R.Gomperts,R.L.Martin,D.J.Fox,T.Keith,M.A.Al-Laham,C.Y.Peng,A.Nanayakkara,C.Gonzalez,M.Challacombe,P.M.W.Gill,B.Johnson,W.Chen,M.W.Wong,J.L.Andres,C.Gonzalez,M.Head-Gordon,E.S.Replogle,J.A.Pople,Gaussian 98,Revision A.9.Gaussian,Inc.,Pittsburgh,PA 1998.
[12]A.R.Katritzky,V.S.Lobanov,M.Karelson,CODESSA:Training Manual,University of Florida,Gainesville,FL 1995.
[13]R.Todeschini,MobyDigs-software for Multilinear Regression Analysis and Variable Subset Selection by Genetic Algorithm,Talete srl,Milan,Italy,2002.
[2]邵学广,蔡文生,《化学信息学》,科学出版社,2005.
[3]缪强,《化学信息学导论》,高等教育出版社,2001.
[4]徐光宪,黎乐民,《量子化学-基本原理和从头计算法》,科学出版社,1985.
[5]C.J.Cramer,Essentials of Computational Chemistry,John WiLey&Sons,New York,2002.
[6]C.K.Majumdar,K.Walter,Nobel Prize in Chemistry in 1998,Current Science 1999,76,1451-1453.
[7]陈凯先,蒋华良,汝运,《计算机辅助药物设计-原理、方法及应用》,上海科技出版社,2000.
[8]陈志行,《有机分子轨道理论》,山东科技出版社,1991.
[9]陈念贻等,《计算化学及其应用》,上海科技出版社,1986.
[10]张德聪,《结构化学》,华南理工大学出版社,2000.
[11]A.Frisch,M.J.Frisch,G.W.Trucks,Gaussian 98 User's Reference,Gaussian.Inc.1998.
[12]W.J.Hehre,R.F.Stewart,J.A.Pople,Self-consistent molecular-orbital methods.I.Use of gaussian expansions of Slater-type atomic orbitals.J.Chem.Phys.1969,51,2657-2664.
[13]J.B.Collins,P.V.R.Schleyer,J.S.Binkley,and J.A.Pople,Self-consistent molecular orbital methods.ⅩⅦ.Geometries and binding energies of second-row molecules.A comparison of three basis sets.J.Chem.Phys.1976,64,5142-5151.
[14]J.S.Binkley,J.A.Pople,W.J.Hehre,Self-consistent molecular orbital methods.21.Small split-valence basis sets for first-row elements.J.Am.Chem.Soc.1980,102,939-974.
[15]M.S.Gordon,J.S.Binkley,J.A.Pople,W.J.Pietro,W.J.Hehre,Self-consistent molecular-orbital methods.22.Small split-valence basis sets for second-row elements.J.Am.Chem.Soc.1982,104,2797-2803.
[16]W.J.Pietro,M.M.Francl,W.J.Hehre,D.J.Defrees,J.A.Pople,J.S.Binkley,Self-consistent molecular orbital methods.24.Supplemented small split-valence basis sets for second-row elements.J.Am.Chem.Soc.1982,104,5039-5048.
[17]K.D.Dobbs,W.J.Hehre,Molecular orbital theory of the properties of inorganic and organcmetallic compounds.4.Extended basis sets for third- and fourth-row,main-group elements.J.Comp.Chem.1986,7,359-378.
[18]K.D.Dobbs,W.J.Hehre,Molecular orbital theory of the properties of inorganic and organometallic compounds.5.Extended basis sets for first-row transition metals.J.Comp.Chem.1987,8,861-879.
[19]K.D.Dobbs,W.J.Hehre,Molecular orbital theory of the properties of inorganic and organometallic compounds.6.Extended basis sets for second-row transition metals.J.Comp.Chem.1987,8,880-893.
[20]R.Ditchfield,W.J.Hehre,J.A.Pople,Self-consistent molecular-orbital methods.Ⅺ.An extended Gaussian-type basis for molecular-orbital studies of organic molecules.J.Chem.Phys.1971,54,724-728.
[21]W.J.Hehre,R.Ditchfield,J.A.Pople,Self-consistent molecular orbital methods.Ⅻ.Further extensions of Gaussian-type basis sets for use in molecular orbital studies of organic molecules.J.Chem.Phys.1972,56,2257-2261.
[22]P.C.Hariharan,J.A.Pople,Accuracy of AHn equilibrium geometries by single determinant molecular orbital theory.Mol.Phys.1974,27,209-214.
[23]M.S.Gordon,The isomers of silacyclopropane.Chem.Phys.Lett.1980,76,163-168.
[24]P.C.Hariharan,J.A.Pople,The influence of polarization functions on molecular orbital hydrogenation energies.Theo.Chim.Acta 1973,28,213-222.
[25]J.P.Blaudeau,M.P.McGrath,L.A.Curtiss,L.Radom,Extension of Gaussian-2(G2) theory to molecules containing third-row atoms K and Ca.J.Chem.Phys.1997,107,5016-5021.
[26]M.M.Francl,W.J.Pietro,W.J.Hehre,J.S.Binkley,D.J.DeFrees,J.A.Pople,M.S.Gordon,Self-consistent molecular orbital methods.ⅩⅩⅢ.A polarization-type basis set for second-row elements.J.Chem.Phys.1982,77,3654-3665.
[27]R.C.Binning,Jr.,L.A.Curtiss,Compact contracted basis sets for third-row atoms:Gallium-krypton.J.Comp.Chem.1990,11,1206-1216.
[28]V.A.Rassolov,J.A.Pople,M.A.Ratner,T.L.Windus,6-31G~* basis set for atoms K through Zn.J.Chem.Phys.1998,109,1223-1229.
[29]V.A.Rassolov,M.A.Ratner,J.A.Pople,P.C.Redfern,L.A.Curtiss,6-31G~*basis set for third-row atoms.J.Comp.Chem.2001,22,976-984.
[30]T.H.Dunning,Jr.,P.J.Hay,in Modern Theoretical Chemistry,Plenum Press,New York,1976.
[31]G.A.Petersson,A.Bennett,T.G.Tensfeldt,M.A.AI-Laham,W.A.Shirley,J.Mantzaris,A complete basis set model chemistry.Ⅰ.The total energies of closed-shell atoms and hydrides of the first-row atoms.J.Chem.Phys.1988,89,2193-2218.
[32]G.A.Petersson,M.A.AI-Laham,A complete basis set model chemistry.Ⅱ.Open-shell systems and the total energies of the fist-row atoms.J.Chem.Phys.1991,94,6081-6090.
[33]K.Raghavachari,G.W.Trucks,Highly correlated systems.Excitation energies of first row transition metals Sc-Cu.J.Chem.Phys.1989,91,1062-1065.
[34]K.Raghavachari,J.A.Pople,E.S.Replogle,M.Head-Gordon,Fifth-order moller-plesset perturbation theory:comparison of existing correlation methods and implementation of new methods correct to fifth-order.J.Chem.Phys.1990,94,5579-5586.
[35]K.Raghavachari,J.A.Pople,E.S.Replogle,M.Head-Gordon,N.C.Handy,Size-consistent brueckner theory limited to double and triple substitutions.Chem.Phys.Lett.1990,167,115-121.
[36]T.Clark,J.Chandrasekhar,G.W.Spitznagel,P.R.Schleyer,Efficient diffuse function-augmented basis sets for anion calculations.Ⅲ.The 3-21G basis set for first-row elements,lithium to fluorine.J.Chem.Phys.1983,4,294-301.
[37]M.J.Frich,J.A.Pople,J.S.Binkley,Self-consistent molecular orbital methods.25.Supplementary functions for Gaussian basis sets.J.Chem.Phys.1984,80,3265-3269.
[38]W.Stevens,H.Basch,J.Krauss,Compact effective potentials and efficient shared-exponent basis sets for the first-and second-row atoms.J.Chem.Phys.1984,81,6026-6033.
[39]W.J.Stevens,M.Krauss,Ⅱ.Basch,P.G.Jasien,Relativistic compact effective potentials and efficient,shared-exponent basis sets for the third-,fourth-,and fifth-row atoms.Can.J.Chem.1992,70,612-630.
[40]T.R.Cundari,W.J.Stevens,Effective core potential methods for the lanthanides.J.Chem.Phys.1993,98,5555-5565.
[41]P.J.Hay,W.R.Wadt,Ab initio effective core potentials for molecular calculations for the transition metal atoms Sc to Hg.J.Chem.Phys.1985,82,270-283.
[42]W.R.Wadt,P.J.Hay,Ab initio effective core potentials for molecular calculations,potentials for main group elements Na to Bi.J.Chem.Phys.1985,82,284-298.
[43]P.J.Hay,W.R.Wadt,Ab initio effective core potentials for molecular calculations.Potentials for K to Au including the outermost core orbitals.J.Chem.Phys.1985,82,299-310.
[44]D.E.Woon,T.H.Dunning,Jr.,Gaussian basis sets for use in correlated molecular calculations.Ⅲ.The second-row atoms,Al-Ar.J.Chem.Phys.1993,98,1358-1371.
[45]R.A.Kendall,T.H.Dunning,Jr.,R.J.Harrison,Electron affinities of the first-row atoms revisited.Systematic basis sets and wave functions.J.Chem.Phys.1992,96,6796-6806.
[46]T.H.Dunning,Jr.,Gaussian basis sets for use in correlated molecular calculations.I.The atoms boron through neon and hydrogen.J.Chem.Phys.1989,90,1007-1023.
[47]K.A.Peterson,D.E.Woon,T.H.Dunning,Jr.,Benchmark calculations with correlated molecular wave functions.IV.The classical barrier height of the H + H_2 →H_2 + H reaction.J.Chem.Phys.1994,100,7410-7415.
[48]A.K.Wilson,T.van Mourik,T.H.Dunning,Jr.,Gaussian basis sets for use in correlated molecular calculations.VI.Sextuple zeta correlation consistent basis sets for boron through neon.J.Mol.Struct.(Theochem) 1997,388,339-349.
[49]E.R.Davidson,Comment on “Comment on Dunning's correlation-consistent basis sets” Chem.Phys.Lett.1996,260,514-518.
[50]A.R.Leach,Molecular Modeling,Addison Wesley Long-man Limited,1996.
[51]R.Hoffmann,An extended H(u|¨)ckel theory.I.Hydrocarbons.J.Chem.Phys.1963,39,1397-1412.
[52]J.A.Pople,D.P.Santry,G.A.Segal,Approximate self-consistent molecular orbital theory .I.Invariant procedures.J.Chem.Phys.1965,43,S129-S135.
[53]J.A.Pople,G.A.Segal,Approximate self-consistent molecular orbital theory.Ⅱ.Calculation with complete neglect of different overlap.J.Chem.Phys.1965,43,S136-S151.
[54]J.A.Pople,G.A.Segal,Approximate self-consistent molecular orbital theory Ⅲ.CNDO results for AB2 and AB3 systems.J.Chem.Phys.1966,44,3289-3296.
[55]J.A.Pople,D.L.Beveridge,P.A.Dobosh,Approximate self-consistent molecular orbital theory V.Intermediate neglect of differential overlap.J.Chem.Phys.1967,47,2026-2033.
[56]M.J.S.Dewar,E.Haselbach,Ground states of σ-bonded molecules.Ⅸ.The MINDO/2 method.J.Am.Chem.Soc.1970,92,590-598.
[57]R.C.Bingham,M.J.S.Dewar,D.H.Lo,Ground states of molecules.J.Am. Chem.Soc.1975,97,1289-1293.
[58]M.J.S.Dewar,Ground states of molecules.38.The MNDO Method.Approximations and Parameters.J.Am.Chem.Soc.1977,99,4899-4907.
[59]M.J.S.Dewar,E.G.Zoebisch,E.F.Healy,J.J.P.Stewart,AMI:A new general purpose quantum mechanical molecular model.J.Am.Chem.Soc.1985,107,3902-3909.
[60]J.J.P.Stewart,Optimization of parameters for semiempirical methods Ⅰ.Method.J.Comp.Chem.1989,10,209-220.
[61]J.J.P.Stewart,Optimization of parameters for semiempirical methods Ⅱ.Applications.J.Comp.Chem.1989,10,221-264.
[62]J.J.P.Stewart,Steawrt Computational Chemistry,2007,http://OpenMOPAC.net.
[63]J.J.P.Stewart,Optimization of parameters for semiempirical methods V:modification of NDDO approximations and application to 70 Elements.J.Mol.Model 2007,13,1173-1213.
[64]R.G.Parr,W.Yang,Density Functional Theory of Atoms and molecules,Oxford University Press,New York,1989.
[65]P.Hohenberg,W.Kohn,Inhomogeneous electron gas.Phys.Rev.1964,136,B864-B871.
[66]W.Kohn,L.J.Sham,Self-consistent equations including exchange and correlation effects.Phys.Rev.1965,140,A1133-A1138.
[67]J.A.Pople,P.M.W.Gill,B.G.Johnson,Kohn-Sham density-functional theory within a finite basis set.Chem.Phys.Lett.1992,199,557-560.
[68]A.D.Becke,Density-functional thermochemistry.Ⅲ.The role of exact exchange.J.Chem.Phys.1993,98,5648-5652.
[69]傅尧,中国科学技术大学博士学位论文,2005.
[70]丁迅雷,中国科学技术大学博士学位论文,2004.
[71]许禄,胡昌玉,《应用化学图论》,北京科学出版社,2000.
[72]王连生,韩朔睽,《分子结构性质与活性》,北京化学工业出版社,1997.
[73]刘焕香,兰州大学博士学位论文,2005.
[74]http://www.nisc.com/cis
[75]http://www.epa.gov/srs
[76]http://www.ccdc.cam.ac.uk
[77]http://ulisse.etoit.eudra.org/Ecdin/Ecdin.html
[78]http://www.bid.med.jhmi.edu/Dan/proteins/pir-last.html
[79]http://www.boc.chem.uu.nl/sugabase/datases.html
[80]http://www.rcsb.org/pdb/Welcome.do
[81]http://www.pubs.acs.org
[82]http://sciencedirect.com
[83]http://www3.interscience.wiley.com/cgi-bin/home
[84]http://www.springerlink.com
[85]http://www.cnki.net/index.htm
[86]http://wanfang.calis.edu.cn/wfkixx/cacp.html
[87]http://www.tydata.com
[88]任月英,兰州大学博士学位论文,2007.
[89]R.W.Kennard,L.A.Stone,Computer aided design of experiments.Technometrics,1969,11,137-148.
[90]R.D.Snee,Validation of regression models:methods and examples.Technometrics,1977,19,415-428.
[91]A.R.Katritzky,V.S.Lobanov,M.Karelson,CODESSA:Reference Manual;Version 2,University of Florida,1994.
[92]D.Rogers,A.J.Hopfinger,Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships.J.Chem.Inf Comput.Sci.1994,34,854-866.
[93]H.Kubinyi,Variable selection in QSAR studies.I.An evolutionary Algorithm.Quant.Struct.-Act.Rel.1994,13,285-294.
[94]J.G.Topliss,R.J.Costello,Chance correlations in structure-activity studies using multiple regression analysis.J.Med.Chem.,1972,15,1066-1068.
[95]王惠文,《偏最小二乘回归方法及其应用[M》,北京国防工业出版社,1999.
[96]姚小军,兰州大学博士学位论文,2005.
[97]R.Wehrens,H.Putter,L.M.C.Buydens,The bootstrap:A tutorial.Chemom.Int. Lab.Syst.2000,54,35-52.
[98]R.Guha,J.R.Serra,P.C.Jurs,Generation of QSAR sets with a self-organizing map.J.Mol.Graph.Model.2004,23,1-14.
[1]W.J.Egan,G.Lauri,Prediction of intestinal permeability.Adv.Drug Delivery Rev. 2002,54,273-289.
[2]M.D.Wessel,P.C.Jurs,J.W.Tolan,S.M.Muskal,Prediction of human intestinal absorption of drug compounds from molecular structure.J.Chem.Inf.Comput.Sci.1998,38,726-735.
[3]T.Hou,J.Wang,W.Zhang,W.Wang,X.Xu,Recent advances in computational prediction of drug absorption and permeability in drug discovery.Curr.Med.Chem.2006,13,2653-2667.
[4]W.P.Walters,M.A.Murcko,Prediction of 'drug-likeness'.Adv.Drug Delivery Rev.2002,54,255-271.
[5]C.Acharya,P.R.Seo,J.E.Polli,A.D.MacKerell,Computational model for predicting chemical substituent effects on passive drug permeability across parallel artificial membranes.Mol.Pharmaceutics 2008,5,818-828.
[6]A.Walter,J.Gutknecht,Permeability of small nonelectrolytes through lipid bilayer membranes.J.Membr.Biol.1986,90,207-217.
[7]I.J.Chen,R.Taneja,D.Yin,P.R.Seo,D.Young,A.D.MacKerell,Jr.,J.E.Polli,Chemical substituent effect on pyridine permeability and mechanistic insight from computational molecular descriptors.Mol.Pharmaceutics 2006,3,745-755.
[8]F.Barbosa,D.Horvath,Molecular similarity and property similarity.Curr.Top.Med.Chem.2004,4,589-600.
[9]A.R.Leach,M.M.Hann,The in silico world of virtual libraries.Drug Discovery Today 2000,5,326-336.
[10]P.Stenberg, U.Norinder, K.Luthman,P.Artursson, Experimental and computational screening models for the prediction of intestinal drug absorption.J.Med.Chem.2001,44,1927-1937.
[11]G.Subramanian,D.B.Kitchen,Computational approaches for modeling human intestinal absorption and permeability.J.Mol.Model.2006,12,577-589.
[12]HyperChem,Release 6.0 for Windows,Hypercube,Inc.,2000.
[13]T.Srl,Dragon for Windows (Software for Molecular Descriptors Calculations)Version 5.4,2006.
[14]R.Todeschini,V.Consonni,Handbook of Molecular Descriptors,Wiley-VCH, Weinheim,Germany,2000.
[1]J.F.Kerr,A.H.Wyllie,A.R.Currie,Apoptosis:a basic biological phenomenon with wide-ranging implications in tissue kinetics.Br.J.Cancer 1972,26,239-257.
[2]H.Steller,Mechanisms and genes of cellular suicide.Science 1995,267,1445-1449.
[3]S.Kothakota,T.Azuma,C.Reinhard,A.Klipel,J.Tang,K.Chu,T.McGarry,M.Kirschner,K.Koths,D.Kwiatkowski,L.Williams,Caspase-3-generated fragment of gelsolin:effector of morphological change in apoptosis.Science 1997,278,294-298.
[4]G.S.Salvesen,V.M.Dixit,Caspases:intracellular signaling by proteolysis.Cell 1997,91,443-446.
[5]P.Villa,S.H.Kaufrnann,W.C.Earnshaw,Caspases and caspase inhibitors.Treds.Biochem.Sci.1997,22,388-393.
[6]L.Herr,K.M.Debatin,Cellular stress response and apoptosis in cancer therapy.Blood 2001,98,2603-2614.
[7]T.Rich,R.L.Allen,A.H.Wyllie,Defying death after DNA damage.Nature 2000,407,777-783.
[8]H.F.Stich,The beneficial and hazardous effects of simple phenolic compounds.Mutat.Res.1991,259,307-324.
[9]C.Hansch,B.Bonavida,A.R.Jazirehi,J.J.Cohen,C.Milliron,A.Kurup,Quantitative structure-activity relationships of phenolic compounds causing apoptosis.Bioorg.Med.Chem.2003,11,617-620.
[10]C.Hansch,A.Jazirehi,S.B.Mekapati,R.Garg,B.Bonavidab,QSAR of apoptosis induction in various cancer cells.Bioorg.Med.Chem.2003,11,3015-3019.
[11]C.D.Selassie,S.Kapur,R.P.Verma,M.Rosario,Cellular apoptosis and cytotoxicity of phenolic compounds:a quantitative structure-activity relationship study.J.Med.Chem.2005,48,7234-7242.
[12]E.Eroglu,H.Turkmen,A DFT-based quantum theoretic QSAR study of aromatic and heterocyclic sulfonamides as carbonic anhydrase inhibitors against isozyme,CA-Ⅱ.J.Mol.Graphics Modell 2007,26,701-708.
[13]J.Wan,L.Zhang,G.F.Yang,Quantitative structure-activity relationships for phenyl triazolinones of protoporphyrinogen oxidase inhibitors:A density functional theory study.J.Comput.Chem.2004,25,1827-1832.
[14]Z.Xi,Z.H.Yu,C.W.Niu,S.R.Ban,G.F.Yang,Development of a general quantumchemical descriptor for steric effects:density functional theory based QSAR study of herbicidal sulfonylurea analogues.J.Comput.Chem.2006,27,1571-1576.
[15]R.G.Parr,W.Yang,Density Functional Theory of Atoms and Molecules,Oxford University Press,Oxfoed,1989.
[16]A.D.Becke,A new mixing of Hartree-Fock and local density-functional theories.J.Chem.Phys.1993,98,1372-1377.
[17]A.D.Becke,Density-functional thermochemistry,Ⅲ.The role of exact exchange.J.Chem.Phys.1993,98,5648-5652.
[18]G.A.Petersson,A.Bennett,T.G.Tensfeldt,M.A.Al-Laham,W.A.Shirley,J.Mantzaris,A complete basis set model chemistry.Ⅰ.The total energies of closed-shell atoms and hydrides of the first-row atoms.J.Chem.Phys.1988,89,2193-2218.
[19]M.J.Frisch,G.W.Trucks,H.B.Schlegel,G.E.Scuseria,M.A.Robb,J.R. Cheeseman,V.G.Zakrzewski,J.A.Montgomery,Jr.,R.E.Stratmann,J.C.Burant,S.Dapprich,J.M.Millam,A.D.Daniels,K.N.Kudin,M.C.Strain,O.Farkas,J.Tomasi,V.Barone,M.Cossi,R.Cammi,B.Mennucci,C.Pomelli,C.Adamo,S.Clifford,J.Ochterski,G.A.Petersson,P.Y.Ayala,Q.Cui,K.Morokuma,D.K.Malick,A.D.Rabuck,K.Raghavachari,J.B.Foresman,J.Cioslowski,J.A.Ortiz,A.G.Baboul,B.B.Stefanov,G Liu,A.Liashenko,P.Piskorz,I.Komaromi,R.Gomperts,R.L.Martin,D.J.Fox,T.Keith,M.A.Al-Laham,C.Y.Peng,A.Nanayakkara,C.Gonzalez,M.Challacombe,P.M.W.Gill,B.Johnson,W.Chen,M.W.Wong,J.L.Andres,C.Gonzalez,M.Head-Gordon,E.S.Replogle,J.A.Pople,Gaussian 98,Revision A.9.Gaussian,Inc.,Pittsburgh,PA 1998.
[20]A.R.Katritzky,V.S.Lobanov,M.Karelson,CODESSA:Training Manual,University of Florida,Gainesville,FL1995.
[21]B.Hemmateenejad,M.A.Safarpour,R.Miri,F.Taghavi,Application of ab initio theory for the QSAR study of 1,4-dihydropyridine-based calcium channel antagonist.J.Comput.Chem.2004,25,1495-1503.
[22]J.Lameira,C.N.Alves,V.Moliner,E.Silla,A density functional study of flavonoid compounds with anti-HIV activity.Eur.J.Med.Chem.2006,41,616-623.
[23]A.B.Sannigrahi,Ab initio Molecular Orbital Calculations of Bond Index and Valency.Adv.Quant.Chem.1992,23,301-351.
[24]R.D.Snee, Validation of regression models: methods and examples.Technometrics 1977,19,415-428.
[25]Y.Y.Ren,H.X.Liu,X.J.Yao,M.C.Liu,Prediction of ozone tropospheric degradation rate constants by projection pursuit regression.Anal.Chim.Acta.2007,589,150-158.
[26]B.Hemmateenejad,R.Miri,M.Akhond,M.Shamsipur,QSAR study of the calcium channel antagonist activity of some recently synthesized dihydropyridine derivatives.An application of genetic algorithm for variable selection in MLR and PLS methods.Chemometr.Intell.Lab.Syst.2002,64,91-99.
[27]O.Deeb,B.Hemmateenejad,A.Jaber,R.G.Juarez,R.Miri,Effect of the electronic and physicochemical parameters on the carcinogenesis activity of some sulfa drugs using QSAR analysis based on genetic-MLR and genetic-PLS.Chemosphere 2007,67,2122-2130.
[28]J.Caballero,L.Fernandez,J.I.Abreu,M.Fernandez,Amino Acid Sequence Autocorrelation vectors and ensembles of Bayesian-Regularized Genetic Neural Networks for prediction of conformational stability of human lysozyme mutants.J.Chem.Inf.Model.2006,46,1255-1268.
[29]M.Fernandez,J.Caballero,Bayesian-regularized genetic neural networks applied to the modelling of non-peptide antagonists for the human luteinizing hormone-releasing hormone receptor.J.Mol.Graph.Model.2006,25,410-422.
[30]L.Fernandez,J.Caballero,J.I.Abreu,M.Fernandez,Amino acid sequence autocorrelation vectors and Bayesian-regularized genetic neural networks for modeling protein conformational stability:gene v protein mutants.Proteins 2007,67,834-852.
[31]R.Todeschini,MobyDigs-software for Multilinear Regression Analysis and Variable Subset Selection by Genetic Algorithm,Talete srl,Milan,Italy,2002.
[32]R.Leardi,R.Boggia,M.Terrile,Genetic algorithms as a strategy for feature selection.J.Chemom.1992,6,267-281.
[33]R.Todeschini,A.Maiocchi,V.Consonni,The K correlation index:theory development and its application in chemometrics.Chemom.Intell.Lab.Syst.1999,46,13-29.
[34]A.J.Miller,Subset Selection in Regression,Chapman & Hall,London,UK 1990.
[35]A.C.Atkinson,Plots,Transformations and Regression,Oxford University Press,Oxford 1985.
[36]H.X.Liu,E.Papa,P.Gramatica,Evaluation and QSAR modeling on multiple endpoints of estrogen activity based on different bioassays.Chemosphere 2008,70,1889-1897.
[37]S.C.Basak,A.T.Balaban,G.D.Grunwald,B.D.Gute,Topological indices:Their nature and mutual relatedness.J.Chem.Inf.Comput.Sci.2000,40, 891-898.
[38]A.R.Katritzky,D.B.Tatham,U.Maran,Theoretical descriptors for the correlation of aquatic toxicity of environmental pollutants by quantitative structure-toxicity relationships.J.Chem.Inf.Comput.Sci.2001,41,1162-1172.
[39]R.C.Weast,Handbook of Chemistry and Physics,CRC Press,Cleveland,1974.
[40]D.T.Stanton,L.M.Egolf,P.C.Jurs,M.G.Hicks,Computer-assisted prediction of normal boiling points of pyrans and pyrroles.J.Chem.Inf.Comput.Sci.1992,32,306-316.
[41]D.T.Stanton,P.C.Jurs,Development and use of charged partial surface area structural descriptors in computer assissted quantitative structure property relationship studies.Anal.Chem.1990,62,2323-2329.
[42]H.Van der Voet,Comparing the predictive accuracy of models using a simple randomization test.Chemom.Intell.Lab.Syst.1994,25,313-323.
[1]S.Pfeiffer,B.Mayer,B.Hemmens,Nitric Oxide:Chemical Puzzles Posed by a Biological Messenger.Angew.Chem.Int.Ed.1999,38,1714-1731.
[2]T.S.Kurtikyan,P.C.Ford,Reactions of nitrogen oxides with heme models:spectral characterization of an elusive five-coordinate Fe~Ⅲ(porphyrin) nitrito intermediate.Angew.Chem.Int.Ed.2006,45,492-496.
[3]T.S.Kurtikyan,A.A.Hovhannisyan,M.E.Hakobyan,J.C.Patterson,A.Iretskii,P.C.Ford,Reactions of nitrogen oxides with the five-coordinate Fe~Ⅲ(porphyrin)nitrito intermediate Fe(Por)(ONO) in sublimed solids.J.Am.Chem.Soc.2007,129,3576-3585.
[4]M.Kirsch,H.-G.Korth,R.Sustmann,H.de Groot,The pathobiochemistry of nitrogen dioxide.Biol.Chem.2002,383,389-399.
[5]S.Pfeiffer,A.Lass,K.Schmidt,B.Mayer,Protein tyrosine nitration in mouse peritoneal macrophages activated in vitro and in vivo:evidence against an essential role of peroxynitrite.FASEBJ.2001,75,2355-2364.
[6]M.G.Espey,S.Xavier,D.D.Thomas,K.M.Miranda,D.A.Wink,Direct real-time evaluation of nitration with green fluorescent protein in solution and within human cells reveals the impact of nitrogen dioxide vs.peroxynitrite mechanisms.Proc.Natl.Acad.Sci.U.S.A.2002,99,3481-3486.
[7]X.Liu,M.J.S.Miller,M.S.Joshi,D.D.Thomas,J.R.Lancaster,Accelerated reaction of nitric oxide with O_2 within the hydrophobic interior of biological membranes.Proc.Natl.Acad.Sci.U.S.A.1998,95,2175-2179.
[8]T.S.Kurtikyan,G.M.Gulyan,G.G.Martirosyan,M.D.Lim,P.C.Ford,Reactions of nitrogen oxides with heme models.Spectral and kinetic study of nitric oxide reactions with solid and solute Fe~Ⅲ(TPP) (NO_3).J.Am.Chem.Soc.2005,127,6216-6224.
[9]X.Li,X.Q.Zhu,F.Zhang,X.X.Wang,J.P.Cheng,Establishment of heterolytic and homolytic Y-NO_2 bond dissociation energy scales of nitro-containing compounds in acetonitrile:chemical origin of NO_2 release and capture.J.Org.Chem.2008,73,2428-2431.
[10]R.Bosque,J.J.Sales,A QSPR study of O-H bond dissociation energy in phenols.Chem.Inf.Comput.Sci.2003,43,637-642.
[11]C.Z.Cao,Y.B.Lin,Evaluation of bond dissociation energy for carbon-hydrogen bond in alkane and its application.Chin.J.Org.Chem.2003,23,207-211.
[12]Y.Fu,L.Liu,B.L.Lin,Y.Mou,Y.H.Cheng,Q.X.Guo,Remote substituent effects on homolytic bond dissociation energies.J.Org.Chem.2003, 68,4657-4662.
[13]P.C.Nam,M.T.Nguyen,A.K.Chandra,Theoretical study of the substituent effects on the S-H bond dissociation energy and ionization energy of 3-pyridinethiol:Prediction of novel antioxidant.J.Phys.Chem.A 2006,110,10904-10911.
[14]F.Agapito,P.M.Nunes,B.J.C.Cabral,R.M.B.d.Santos,J.A.M.Sim(?)es, Energetics of the allyl group.J.Org.Chem.2007,72,8770-8779.
[15]J.X.Shao,X.L.Cheng,X.D.Yang,Calculations of the bond dissociation energies for NO_2 scission in some nitro compounds.Struct.Chem.2005,16,457-460.
[16]J.X.Shao,X.L.Cheng,X.D.Yang,The C-NO_2 bond dissociation energies of some nitroaromatic compounds:DFT study.Struct.Chem.2006,17,547-550.
[17]J.X.Shao,X.L.Cheng,X.D.Yang,Density functional calculations of bond dissociation energies for removal of the nitrogen dioxide moiety in some nitroaromatic molecules.J.Mol.Struct.(Theochem) 2005,755,127-130.
[18]H.J.Chen,X.L.Cheng,Z.G.Ma,X.F.Su,Theoretical studies of C-NO_2 bond dissociation energies for chain nitro compounds.J.Mol.Struct.(Theochem) 2007,807,43-47.
[19]M.J.Frisch,G.W.Trucks,H.B.Schlegel,G.E.Scuseria,M.A.Robb,J.R.Cheeseman,V.G Zakrzewski,J.A.Montgomery,Jr.,R.E.Stratmann,J.C.Burant,S.Dapprich,J.M.Millam,A.D.Daniels,K.N.Kudin,M.C.Strain,O.Farkas,J.Tomasi,V.Barone,M.Cossi,R.Cammi,B.Mennucci,C.Pomelli,C.Adamo,S.Clifford,J.Ochterski,G.A.Petersson,P.Y.Ayala,Q.Cui,K.Morokuma,D.K.Malick,A.D.Rabuck,K.Raghavachari J.B.Foresman,J.Cioslowski,J.A.Ortiz,A.G.Baboul,B.B.Stefanov,G.Liu,A.Liashenko,P.Piskorz,I.Komaromi,R.Gomperts,R.L.Martin,D.J.Fox,T.Keith,M.A.Al-Laham,C.Y.Peng,A.Nanayakkara,C.Gonzalez,M.Challacombe,P.M.W.Gill,B.Johnson,W.Chen,M.W.Wong,J.L.Andres,C.Gonzalez,M.Head-Gordon,E.S.Replogle,J.A.Pople,Gaussian 98,Revision A.9.Gaussian,Inc.,Pittsburgh,PA 1998.
[20]Y.Y.Ren,H.X.Liu,X.J.Yao,M.C.Liu,Prediction of ozone tropospheric degradation rate constants by projection pursuit regression.Anal.Chim.Acta 2007,589,150-158.
[1]I.M.Konen,I.B.Pollack,E.X.J.Li,M.E.Vamer,J.F.Stanton,Infrared overtone spectroscopy and unimolecular decay dynamics of peroxynitrous acid.J.Chem.Phys.2005,122,094320/1-094320/16.
[2]P.C.Do Couto,B.J.C.Cabral,J.A.M.Sim(?)es,S-H bond dissociation enthalpies:The importance of a complete basis set approach.Chem.Phys.Lett.2006,421,504-507.
[3]P.C.Nam,M.T.Nguyen,A.K.Chandra,Effect of substituents on the P-H bond dissociation enthalpies of phenylphosphines and proton affinities of phenylphosphine anions:A DFT study.J.Phys.Chem.A 2004,108,11362-11368.
[4]Y.M.Wang,Y.Fu,L.Liu,Q.X.Guo,Substituent effects on the ring opening of 2-aziridinylmethyl radicals.J.Org.Chem.2005,70,3633-3640.
[5]F.Agapito,P.M.Nunes,B.J.C.Cabral,R.M.B.d.Santos,J.A.M.SimOes,Energetics of the allyl group.J.Org.Chem.2007,72,8770-8779.
[6]M.J.Li,L.Liu,Y.Fu,Q.X.Guo,Development of an ONIOM-G3B3 method to accurately predict C-H and N-H bond dissociation enthalpies of ribonucleosides and deoxyribonucleosides.7.Phys.Chem.5 2005,109,13818-13826.
[7]Y.Feng,L.Liu,J.T.Wang,H.Huang,Q.X.Guo,Assessment of experimental bond dissociation energies using composite ab Initio methods and evaluation of the performances of density functional methods in the calculation of bond dissociation energies.J.Chem.Inf.Comput.Sci.2003,43,2005-2013.
[8]D.S.Gabriel,W.B.Joseph,Thermochemistry,bond Energies,and internal rotor potentials of dimethyl tetraoxide.J.Phys.Chem.A 2007,111,12026-12036.
[10]Y.R.Luo,Comprehensive Handbook of Chemical Bond Energies,CRC Press:London,U.K.,2007.
[11]M.J.Frisch,G.W.Trucks,H.B.Schlegel,G E.Scuseria,M.A.Robb,J.R.Cheeseman,V.G.Zakrzewski,J.A.Montgomery,Jr.,R.E.Stratmann,J.C.Burant,S.Dapprich,J.M.Millam,A.D.Daniels,K.N.Kudin,M.C.Strain,O.Farkas,J.Tomasi,V.Barone,M.Cossi,R.Cammi,B.Mennucci,C.Pomelli,C.Adamo,S.Clifford,J.Ochterski,G.A.Petersson,P.Y.Ayala,Q.Cui,K.Morokuma,D.K.Malick,A.D.Rabuck,K.Raghavachari,J.B.Foresman,J.Cioslowski,J.A.Ortiz,A.G.Baboul,B.B.Stefanov,G Liu,A.Liashenko,P.Piskorz,I.Komaromi,R.Gomperts,R.L.Martin,D.J.Fox,T.Keith,M.A.Al-Laham,C.Y.Peng,A.Nanayakkara,C.Gonzalez,M.Challacombe,P.M.W.Gill,B.Johnson,W.Chen,M.W.Wong,J.L.Andres,C.Gonzalez,M.Head-Gordon,E.S.Replogle,J.A.Pople,Gaussian 98,Revision A.9.Gaussian,Inc.,Pittsburgh,PA 1998.
[12]A.R.Katritzky,V.S.Lobanov,M.Karelson,CODESSA:Training Manual,University of Florida,Gainesville,FL 1995.
[13]R.Todeschini,MobyDigs-software for Multilinear Regression Analysis and Variable Subset Selection by Genetic Algorithm,Talete srl,Milan,Italy,2002.