细胞色素P450酶多态性数据库构建及相关药物代谢研究
|
摘要
细胞色素P450酶家族是人体中重要的一类单氧化酶,在体内发挥着许多功能,特别在药物代谢过程中具有重要作用,是人体内主要的药物代谢酶。同时此类酶的另一特性是在基因水平上具有广泛的遗传多样性,可以引起不同个体之间药物代谢能力的明显差异。因此对于细胞色素P450酶介导的药物代谢过程、不同细胞色素P450酶单体与化合物之间的代谢关系、基因多态性对于细胞色素P450酶的功能影响以及不同细胞色素P450酶突变体的活性改变机制等一直是人们对于细胞色素P450酶研究的热点。本文主要针对细胞色素P450酶的非同义单核苷酸多态性对于酶功能活性的影响及细胞色素P450酶与不同化合物之间的代谢关系进行四方面相对独立的研究,下面对进行的研究内容和所得到的结论进行简要的描述。
1、通过收集和阅读相关文献,构建了侧重于细胞色素P450酶的非同义单核苷酸多态性(nsSNP)影响酶活性变化的数据库CYP-nsSNP。该数据库不仅对已测定的相关实验数据进行了有效的整理,同时也可以为理论研究氨基酸在维持细胞色素P450酶活性中的作用提供了可靠的数据资源;
2、利用分子动力学模拟和分子对接以及其它基于蛋白结构的方法对于蛋白表面具有重要作用的氨基酸突变F186L如何影响CYP1A2结构和功能进行了系统研究。从蛋白结构和蛋白运动的角度上分析了该表面氨基酸突变对于酶活性的作用,在原子水平上对于此表面氨基酸突变导致酶活性改变给予了合理的解释,并且首次在细胞色素P450酶研究中将蛋白运动和底物通道相结合进行分析。同时提出了与别构效应调节相类似,表面氨基酸突变可以借助影响蛋白运动和改变蛋白构象的方式来调节蛋白活性;
3、利用机器学习方法从化合物结构出发对于不同细胞色素P450酶底物代谢的选择性进行研究。将遗传算法和人工神经网络方法以及多标签K邻近分类法联合使用,分别构建出可以对细胞色素P450酶底物进行分类的单标签多类别和多标签多类别分类模型。与其它细胞色素P450酶底物的分类模型相比,我们的模型涵盖了更多种类的细胞色素P450酶,更加符合体内细胞色素P450酶所介导的药物代谢;
4、将基于蛋白结构和小分子结构的两类方法相结合,构建出针对CYP1A2酶活性中心的结构模型。通过该模型我们可以获得组成CYP1A2酶活性中心的重要氨基酸残基在底物结合过程中所发挥的作用,并且对于药物代谢位点预测、药物设计以及有目的酶功能改造提供了详实可靠的信息。
The cytochrome P450 superfamily (CYP) is a group of heme-containing monooxygenases which perform many necessary functions in the human body. As the major drug-metabolizing enzymes, CYP enzymes are responsible for the metabolism of a large number of drugs. In addition, CYP enzymes are subject to genetic polymorphism resulting in the inter-individual difference in drug-metabolizing ability. Thus, the main focus of recent CYP research includes the CYP-mediated drug metabolism, the substrate specificity of different CYP isoenzymes, the influences of different genetic polymorphisms on function of CYP enzymes and the possible mechanism for changing enzymatic activity of CYP due to mutation of amino acid. Here we carried out four independent experiments focused on the effect of non-synonymous single nucleotide polymorphism (nsSNP) on the enzymatic activity of CYP and the substrate selectivity of different CYP isoenzymes. These studies and their conclusions are briefly described below.
1. A database named CYP-nsSNP was constructed through collecting the relevant data from the published references. The CYP-nsSNP is used to organize the available data regarding effect of nsSNPs on function of CYP proteins and to provide the reliable information for theoretical investigation of the role of amino acids in CYP function.
2. The effect of a surface mutation F186L on CYP1A2 structure and function was explored using the molecular dynamics simulation and molecular docking as well as other structure-based methods. In this study, the long-range effect of surface mutation was comprehensively investigated from the point of view of protein structure and motions. Additionally, the method of protein motion combined with substrate channel was firstly applied to reveal the relationship between structure and function of CYP protein. Based on results from this study, we can provide a rational explanation for the decrease in enzymatic activity caused by mutation. In addition, we also propose a new mechanism for alosteric regulation of enzyme induced by mutation through changing the access channels and protein conformations.
3. The substrate selectivity of different CYP isoenzymes was investigated using the machine learning methods based on the structure of CYP substrates. The genetic algorithm was combined with the artificial neural network and multi-label K nearest neighbour method to construct the single-label multi-class and multi-label multi-class classification models. Compared with the traditional models, two models reflect the more realistic CYP-mediated drugs metabolism in the human body. After appropriate evaluation, both models exhibited more than 80% of predictive accuracy.
4. Integrating the information about both protein and compounds, we constructed a structural model specific to CYP1A2 active site using the comparative molecular field analysis. Based on such a model, we can investigate the detailed role of residues lining the CYP1A2 active site in substrate binding. Therefore, such analysis is useful for the rational drug design and enzyme modification by providing the detailed and reliable information about protein-ligand interactions.
1、通过收集和阅读相关文献,构建了侧重于细胞色素P450酶的非同义单核苷酸多态性(nsSNP)影响酶活性变化的数据库CYP-nsSNP。该数据库不仅对已测定的相关实验数据进行了有效的整理,同时也可以为理论研究氨基酸在维持细胞色素P450酶活性中的作用提供了可靠的数据资源;
2、利用分子动力学模拟和分子对接以及其它基于蛋白结构的方法对于蛋白表面具有重要作用的氨基酸突变F186L如何影响CYP1A2结构和功能进行了系统研究。从蛋白结构和蛋白运动的角度上分析了该表面氨基酸突变对于酶活性的作用,在原子水平上对于此表面氨基酸突变导致酶活性改变给予了合理的解释,并且首次在细胞色素P450酶研究中将蛋白运动和底物通道相结合进行分析。同时提出了与别构效应调节相类似,表面氨基酸突变可以借助影响蛋白运动和改变蛋白构象的方式来调节蛋白活性;
3、利用机器学习方法从化合物结构出发对于不同细胞色素P450酶底物代谢的选择性进行研究。将遗传算法和人工神经网络方法以及多标签K邻近分类法联合使用,分别构建出可以对细胞色素P450酶底物进行分类的单标签多类别和多标签多类别分类模型。与其它细胞色素P450酶底物的分类模型相比,我们的模型涵盖了更多种类的细胞色素P450酶,更加符合体内细胞色素P450酶所介导的药物代谢;
4、将基于蛋白结构和小分子结构的两类方法相结合,构建出针对CYP1A2酶活性中心的结构模型。通过该模型我们可以获得组成CYP1A2酶活性中心的重要氨基酸残基在底物结合过程中所发挥的作用,并且对于药物代谢位点预测、药物设计以及有目的酶功能改造提供了详实可靠的信息。
The cytochrome P450 superfamily (CYP) is a group of heme-containing monooxygenases which perform many necessary functions in the human body. As the major drug-metabolizing enzymes, CYP enzymes are responsible for the metabolism of a large number of drugs. In addition, CYP enzymes are subject to genetic polymorphism resulting in the inter-individual difference in drug-metabolizing ability. Thus, the main focus of recent CYP research includes the CYP-mediated drug metabolism, the substrate specificity of different CYP isoenzymes, the influences of different genetic polymorphisms on function of CYP enzymes and the possible mechanism for changing enzymatic activity of CYP due to mutation of amino acid. Here we carried out four independent experiments focused on the effect of non-synonymous single nucleotide polymorphism (nsSNP) on the enzymatic activity of CYP and the substrate selectivity of different CYP isoenzymes. These studies and their conclusions are briefly described below.
1. A database named CYP-nsSNP was constructed through collecting the relevant data from the published references. The CYP-nsSNP is used to organize the available data regarding effect of nsSNPs on function of CYP proteins and to provide the reliable information for theoretical investigation of the role of amino acids in CYP function.
2. The effect of a surface mutation F186L on CYP1A2 structure and function was explored using the molecular dynamics simulation and molecular docking as well as other structure-based methods. In this study, the long-range effect of surface mutation was comprehensively investigated from the point of view of protein structure and motions. Additionally, the method of protein motion combined with substrate channel was firstly applied to reveal the relationship between structure and function of CYP protein. Based on results from this study, we can provide a rational explanation for the decrease in enzymatic activity caused by mutation. In addition, we also propose a new mechanism for alosteric regulation of enzyme induced by mutation through changing the access channels and protein conformations.
3. The substrate selectivity of different CYP isoenzymes was investigated using the machine learning methods based on the structure of CYP substrates. The genetic algorithm was combined with the artificial neural network and multi-label K nearest neighbour method to construct the single-label multi-class and multi-label multi-class classification models. Compared with the traditional models, two models reflect the more realistic CYP-mediated drugs metabolism in the human body. After appropriate evaluation, both models exhibited more than 80% of predictive accuracy.
4. Integrating the information about both protein and compounds, we constructed a structural model specific to CYP1A2 active site using the comparative molecular field analysis. Based on such a model, we can investigate the detailed role of residues lining the CYP1A2 active site in substrate binding. Therefore, such analysis is useful for the rational drug design and enzyme modification by providing the detailed and reliable information about protein-ligand interactions.
引文
[1] Seastedt T. The role of microarthropods in decomposition and mineralization processes. Annual Review of Entomology. 1984, 29(1): 25-46.
[2]许化夏,李培军,刘宛,宋玉芳.生物细胞色素P450的研究进展.农业环境保护. 2002, 2(12): 188-191.
[3] Estabrook R.W. A passion for P450s (remembrances of the early history of research on cytochrome P450). Drug Metabolism and Disposition. 2003, 31(12): 1461-1473.
[4] Miller J.A. The metabolism of xenobiotics to reactive electrophiles in chemical carcinogenesis and mutagenesis: a collaboration with Elizabeth Cavert Miller and our associates. Drug metabolism reviews. 1998, 30(4): 645-674.
[5] Mueller G.C.,Miller J. The reductive cleavage of 4-dimethylaminoazobenzene by rat liver: the intracellular distribution of the enzyme system and its requirement for triphosphopyridine nucleotide. Journal of Biological Chemistry. 1949, 180(3): 1125-1136.
[6] Mueller G.C.,Miller J. The Metabolism of Methylated Aminoazo Dyes. Journal of Biological Chemistry. 1953, 202(2): 579-587.
[7] Axelrod J. The enzymatic demethylation of ephedrine. Journal of Pharmacology and Experimental Therapeutics. 1955, 114(4): 430-438.
[8] Gillette J.R. Laboratory of Chemical Pharmacology, National Heart, Lung, and Blood Institute, NIH: A Short History. Annual Review of Pharmacology and Toxicology. 2000, 40(1): 19-41.
[9] Ryan K.J.,Engel L.L. Hydroxylation of steroids at carbon 21. Journal of Biological Chemistry. 1957, 225(1): 103-114.
[10] Mason H.,Fowlks W.,Peterson E. Oxygen transfer and electron transport by the phenolase complex1 Journal of the American Chemical Society. 1955, 77(10): 2914-2915.
[11] Hayaishi O.,Katagiri M.,Rothberg S. Mechanism of the pyrocatechase reaction. Journal of the American Chemical Society. 1955, 77(20): 5450-5451.
[12] Chance B. Techniques for the assay of the respiratory enzymes. Methods Enzymol. 1957, 4273-329.
[13] Chance B. Rapid and Sensitive Spectrophotometry. I. The Accelerated and Stopped‐ Flow Methods for the Measurement of the Reaction Kinetics and Spectra of Unstable Compounds inthe Visible Region of the Spectrum. Review of Scientific Instruments. 1951, 22(8): 619-627.
[14] Estabrook R.W. Mitochondrial respiratory control and the polarographic measurement of ADP: O ratios. Methods in enzymology. 1967, 1041-47.
[15] Klingenberg M. Pigments of rat liver microsomes. Archives of biochemistry and biophysics. 1958, 75(2): 376-386.
[16] Cooper D.,Estabrook R.,Rosenthal O. On the cytochromes in microsomes from cortex and medulla of steer adrenals. 1963, 22587.
[17] Omura T.,Sato R. A new cytochrome in liver microsomes. Journal of Biological Chemistry. 1962, 237(4): 1375-1376.
[18] Remmer H.,Merker H. Effect of drugs on the formation of smooth endoplasmic reticulum and drug-metabolizing enzymes. Annals of the New York Academy of Sciences. 1965, 123(Evaluation and Mechanisms of Drug Toxicity): 79-97.
[19] Cooper D.Y.,Levin S.,Narasimhulu S., et al. Photochemical action spectrum of the terminal oxidase of mixed function oxidase systems. Science. 1965, 147(3656): 400-402.
[20] Lu A.,Coon M. Role of hemoprotein P-450 in fatty acid omega-hydroxylation in a soluble enzyme system from liver microsomes. J Biol Chem. 1968, 32(243): 1331-1332.
[21] Porter T.D. Jud Coon: 35 years of P450 research, a synopsis of P450 history. Drug Metabolism and Disposition. 2004, 32(1): 1-6.
[22] Haugen D.,Van der Hoeven T.,Coon M. Purified liver microsomal cytochrome P-450. Separation and characterization of multiple forms. Journal of Biological Chemistry. 1975, 250(9): 3567-3570.
[23] Haugen D.,Coon M.J. Properties of electrophoretically homogeneous phenobarbital-inducible and beta-naphthoflavone-inducible forms of liver microsomal cytochrome P-450. Journal of Biological Chemistry. 1976, 251(24): 7929-7939.
[24] Lewis D.F.V. 57 varieties: the human cytochromes P450. pgs. 2004, 5(3): 305-318.
[25] Iyanagi T.,Mason H. Properties of hepatic reduced nicotinamide adenine dinucleotide phosphate-cytochrome c reductase. Biochemistry. 1973, 12(12): 2297-2308.
[26] Coon M.J.,Strobel H.W.,Boyer R.F. On the mechanism of hydroxylation reactions catalyzed by cytochrome P-450. Drug Metabolism and Disposition. 1973, 1(1): 92-97.
[27] Vermilion J.L.,Coon M.J. Purified liver microsomal NADPH-cytochrome P-450 reductase. Spectral characterization of oxidation-reduction states. Journal of Biological Chemistry. 1978, 253(8): 2694-2704.
[28] Vermilion J.,Ballou D.,Massey V., et al. Separate roles for FMN and FAD in catalysis by liver microsomal NADPH-cytochrome P-450 reductase. Journal of Biological Chemistry. 1981, 256(1): 266-277.
[29] White R.,Coon M. Oxygen activation by cytochrome P-450. Annual review of biochemistry. 1980, 49315-356.
[30] Khani S.C.,Zaphiropoulos P.G.,Fujita V.S., et al. cDNA and derived amino acid sequence of ethanol-inducible rabbit liver cytochrome P-450 isozyme 3a (P-450ALC). Proceedings of the National Academy of Sciences of the United States of America. 1987, 84(3): 638-642.
[31] Khani S.,Porter T.,Fujita V., et al. Organization and differential expression of two highly similar genes in the rabbit alcohol-inducible cytochrome P-450 subfamily. Journal of Biological Chemistry. 1988, 263(15): 7170-7175.
[32] Porter T.D.,Khani S.,Coon M.J. Induction and tissue-specific expression of rabbit cytochrome P450IIE1 and IIE2 genes. Molecular pharmacology. 1989, 36(1): 61-65.
[33] Nebert D.W.,Adesnik M.,Coon M.J., et al. The P450 gene superfamily: recommended nomenclature. Dna. 1987, 6(1): 1-11.
[34] Cosme J.,Johnson E.F. Engineering microsomal cytochrome P450 2C5 to be a soluble, monomeric enzyme. Journal of Biological Chemistry. 2000, 275(4): 2545-2553.
[35] Williams P.A.,Cosme J.,Sridhar V., et al. Mammalian Microsomal Cytochrome P450 Monooxygenase:: Structural Adaptations for Membrane Binding and Functional Diversity. Molecular Cell. 2000, 5(1): 121-131.
[36] Nelson D.R. The cytochrome P450 homepage. Human Genomics. 2009, 4(1): 59-65.
[37] Nelson D.,Koymans L.,Kamataki T., et al. IC Gunsalus & DW Nebert: P450 superfamily: update on new sequences, gene mapping, accession numbers and nomenclature. Pharmacogenetics. 1996, 61-42.
[38] Nelson D.R.,Kamataki T.,waxman D.J., et al. The P450 superfamily: update on new sequences, gene mapping, accession numbers, early trivial names of enzymes, and nomenclature. DNA and Cell Biology. 1993, 12(1): 1-51.
[39] De Montellano P.R.O. Cytochrome P450: structure, mechanism, and biochemistry. Plenum Pub Corp. 2005: 585-617.
[40] Nelson D.R.,Schuler M.A.,Paquette S.M., et al. Comparative genomics of rice and Arabidopsis. Analysis of 727 cytochrome P450 genes and pseudogenes from a monocot and a dicot. Plant Physiology. 2004, 135(2): 756-772.
[41] Tijet N.,Helvig C.,Feyereisen R. The cytochrome P450 gene superfamily in Drosophila melanogaster: annotation, intron-exon organization and phylogeny. Gene. 2001, 262(1-2): 189-198.
[42] Claudianos C.,Ranson H.,Johnson R., et al. A deficit of detoxification enzymes: pesticide sensitivity and environmental response in the honeybee. Insect Molecular Biology. 2006, 15(5): 615-636.
[43] Paquette S.M.,Bak S.,Feyereisen R. Intron-exon organization and phylogeny in a large superfamily, the paralogous cytochrome P450 genes of Arabidopsis thaliana. DNA and Cell Biology. 2000, 19(5): 307-317.
[44] Schuler M.A.,Werck-Reichhart D. Functional genomics of P450s. Annual Review of Plant Biology. 2003, 54(1): 629-667.
[45] Nelson D.R.,Zeldin D.C.,Hoffman S.M.G., et al. Comparison of cytochrome P450 (CYP) genes from the mouse and human genomes, including nomenclature recommendations for genes, pseudogenes and alternative-splice variants. Pharmacogenetics and Genomics. 2004, 14(1): 1-18.
[46] Debeljak N. , Fink M. , Rozman D. Many facets of mammalian lanosterol 14 [alpha]-demethylase from the evolutionarily conserved cytochrome P450 family CYP51. Archives of biochemistry and biophysics. 2003, 409(1): 159-171.
[47] Waterman M.R.,Lepesheva G.I. Sterol 14 [alpha]-demethylase, an abundant and essential mixed-function oxidase. Biochemical and biophysical research communications. 2005, 338(1): 418-422.
[48] Poulos T.L.,Finzel B.C.,Howard A.J. High-resolution crystal structure of cytochrome P450cam. Journal of molecular biology. 1987, 195(3): 687-700.
[49] Pochapsky T.C.,Kazanis S.,Dang M. Conformational Plasticity and Structure/Function Relationships in Cytochromes P450. Antioxidants & Redox Signaling. 2010, 13(8): 1273-1296.
[50]王斌,李德远.细胞色素P450的结构与催化机理.有机化学. 2009, 29(004): 658-662.
[51] Sigel A.,Sigel H.,Sigel R.K.O. The ubiquitous roles of cytochrome P450 proteins. West Sussex: Wiley. 2007: 27-53.
[52] Negishi M.,Iwasaki M.,Juvonen R.O., et al. Structural flexibility and functional versatility of cytochrome P450 and rapid evolution. Mutation Research/Fundamental and MolecularMechanisms of Mutagenesis. 1996, 350(1): 43-50.
[53] Baudry J.,Rupasinghe S.,Schuler M.A. Class-dependent sequence alignment strategy improves the structural and functional modeling of P450s. Protein Engineering Design and Selection. 2006, 19(8): 345-353.
[54] Lindberg R.L.P.,Negishi M. Alteration of mouse cytochrome P450coh substrate specificity by mutation of a single amino-acid residue. Nature. 1989, (339): 632-634.
[55] Schalk M.,Croteau R. A single amino acid substitution (F363I) converts the regiochemistry of the spearmint (-)-limonene hydroxylase from a C6-to a C3-hydroxylase. Proceedings of the National Academy of Sciences of the United States of America. 2000, 97(22): 11948-11953.
[56] Domanski T.,Halpert J. Analysis of mammalian cytochrome P450 structure and function by site-directed mutagenesis. Current Drug Metabolism. 2001, 2(2): 117-137.
[57] Rupasinghe S.,Schuler M.A. Homology modeling of plant cytochrome P450s. Phytochemistry Reviews. 2006, 5(2): 473-505.
[58] Gilbert L.I. Halloween genes encode P450 enzymes that mediate steroid hormone biosynthesis in Drosophila melanogaster. Molecular and cellular endocrinology. 2004, 215(1-2): 1-10.
[59] Scott J.G.,Wen Z. Cytochromes P450 of insects: the tip of the iceberg. Pest management science. 2001, 57(10): 958-967.
[60] Schuler M.A.,Duan H.,Bilgin M., et al. Arabidopsis cytochrome P450s through the looking glass: a window on plant biochemistry. Phytochemistry Reviews. 2006, 5(2): 205-237.
[61] Fujioka S. , Sakurai A. Biosynthesis and metabolism of brassinosteroids. Physiologia Plantarum. 1997, 100(3): 710-715.
[62] Szekeres M.,Németh K.,Koncz-Kálmán Z., et al. Brassinosteroids rescue the deficiency of CYP90, a cytochrome P450, controlling cell elongation and de-etiolation in Arabidopsis. Cell. 1996, 85(2): 171-182.
[63] Choe S.,Dilkes B.P.,Fujioka S., et al. The DWF4 gene of Arabidopsis encodes a cytochrome P450 that mediates multiple 22 a-hydroxylation steps in brassinosteroid biosynthesis. The Plant Cell Online. 1998, 10(2): 231-243.
[64] Kim T.W.,Hwang J.Y.,Kim Y.S., et al. Arabidopsis CYP85A2, a cytochrome P450, mediates the Baeyer-Villiger oxidation of castasterone to brassinolide in brassinosteroid biosynthesis. The Plant Cell Online. 2005, 17(8): 2397-2412.
[65] Nomura T.,Kushiro T.,Yokota T., et al. The last reaction producing brassinolide is catalyzed by cytochrome P-450s, CYP85A3 in tomato and CYP85A2 in Arabidopsis. Journal ofBiological Chemistry. 2005, 280(18): 17873-17879.
[66] Niwa R.,Matsuda T.,Yoshiyama T., et al. CYP306A1, a cytochrome P450 enzyme, is essential for ecdysteroid biosynthesis in the prothoracic glands of Bombyx and Drosophila. Journal of Biological Chemistry. 2004, 279(34): 35942-35949.
[67] Warren J.T.,Petryk A.,Marqués G., et al. Phantom encodes the 25-hydroxylase of Drosophila melanogaster and Bombyx mori: a P450 enzyme critical in ecdysone biosynthesis. Insect biochemistry and molecular biology. 2004, 34(9): 991-1010.
[68] Namiki T.,Niwa R.,Sakudoh T., et al. Cytochrome P450 CYP307A1/Spook: a regulator for ecdysone synthesis in insects. Biochemical and biophysical research communications. 2005, 337(1): 367-374.
[69] Choi M.H. , Skipper P.L. , Wishnok J.S., et al. Characterization of testosterone 11β-hydroxylation catalyzed by human liver microsomal cytochromes P450. Drug Metabolism and Disposition. 2005, 33(6): 714-718.
[70] Turk E.M.,Fujioka S.,Seto H., et al. CYP72B1 inactivates brassinosteroid hormones: an intersection between photomorphogenesis and plant steroid signal transduction. Plant Physiology. 2003, 133(4): 1643-1653.
[71] Nakamura M.,Satoh T.,Tanaka S.I., et al. Activation of the cytochrome P450 gene, CYP72C1, reduces the levels of active brassinosteroids in vivo. Journal of experimental botany. 2005, 56(413): 833-840.
[72] Williams D.R.,Fisher M.J.,Rees H.H. Characterization of ecdysteroid 26-hydroxylase: an enzyme involved in molting hormone inactivation. Archives of biochemistry and biophysics. 2000, 376(2): 389-398.
[73] Wen Z.,Pan L.,Berenbaum M.R., et al. Metabolism of linear and angular furanocoumarins by Papilio polyxenes CYP6B1 co-expressed with NADPH cytochrome P450 reductase. Insect biochemistry and molecular biology. 2003, 33(9): 937-947.
[74] Li X.,Baudry J.,Berenbaum M.R., et al. Structural and functional divergence of insect CYP6B proteins: From specialist to generalist cytochrome P450. Proceedings of the National Academy of Sciences of the United States of America. 2004, 101(9): 2939-2944.
[75] Yano J.K.,Hsu M.H.,Griffin K.J., et al. Structures of human microsomal cytochrome P450 2A6 complexed with coumarin and methoxsalen. Nature Structural & Molecular Biology. 2005, 12(9): 822-823.
[76] Gustafsson M.C.U. , Roitel O. , Marshall K.R., et al. Expression, Purification, andCharacterization of Bacillus subtilis Cytochromes P450 CYP102A2 and CYP102A3: Flavocytochrome Homologues of P450 BM3 from Bacillus megaterium. Biochemistry. 2004, 43(18): 5474-5487.
[77] Scheller U.,Zimmer T.,K rgel E., et al. Characterization of then-Alkane and Fatty Acid Hydroxylating Cytochrome P450 Forms 52A3 and 52A4. Archives of biochemistry and biophysics. 1996, 328(2): 245-254.
[78] Salaün J.,Helvig C. Cytochrome P450-dependent oxidation of fatty acids. Drug metabolism and drug interactions. 1995, 12(3-4): 261-283.
[79] Duan H.,Schuler M.A. Differential expression and evolution of the Arabidopsis CYP86A subfamily. Plant Physiology. 2005, 137(3): 1067-1081.
[80] Xiao F.,Goodwin S.M.,Xiao Y., et al. Arabidopsis CYP86A2 represses Pseudomonas syringae type III genes and is required for cuticle development. The EMBO Journal. 2004, 23(14): 2903-2913.
[81] Kandel S. , Morant M. , Benveniste I., et al. Cloning, functional expression, and characterization of CYP709C1, the first sub-terminal hydroxylase of long chain fatty acid in plants. Journal of Biological Chemistry. 2005, 280(43): 35881-35889.
[82] Oktia R.,Okita J. Cytochrome P450 4A fatty acid omega hydroxylases. Current Drug Metabolism. 2001, 2(3): 265-281.
[83] Henne K.R.,Kunze K.L.,Zheng Y.M., et al. Covalent Linkage of Prosthetic Heme to CYP4 Family P450 Enzymes. Biochemistry. 2001, 40(43): 12925-12931.
[84] Tomaszewski P. , Kubiak-Tomaszewska G. , Pachecka J. Cytochrome P450 polymorphism--molecular, metabolic, and pharmacogenetic aspects. II. Participation of CYP isoenzymes in the metabolism of endogenous substances and drugs. Acta Poloniae Pharmaceutica. 2008, 65(3): 307-318.
[85] Guengerich F. Cytochrome P450 enzymes in the generation of commercial products. Nature Reviews Drug Discovery. 2002, 1(5): 359-366.
[86] Weide J.v.d.,Steijns L.S.W. Cytochrome P450 enzyme system: genetic polymorphisms and impact on clinical pharmacology. Annals of clinical biochemistry. 1999, 36722-729.
[87] Issa A. Personalized Medicine and the Practice of Medicine in the 21st Century. McGill Journal of Medicine. 2007, 10(1): 53-57.
[88] Ingelman-Sundberg M. The human genome project and novel aspects of cytochrome P450 research. Toxicology and Applied Pharmacology. 2005, 207(2): 52-56.
[89] Nelson D.,Zeldin D.,Hoffman S., et al. Comparison of cytochrome P450 (CYP) genes from the mouse and human genomes, including nomenclature recommendations for genes, pseudogenes and alternative-splice variants. Pharmacogenetics. 2004, 14(1): 1-18.
[90] Yao A.,Charlab R.,Li P. Systematic identification of pseudogenes through whole genome expression evidence profiling. Nucleic Acids Research. 2006, 34(16): 4477-4485.
[91] Shimizu T.,Ochiai H.,?sell F., et al. Bioinformatics research on inter-racial difference in drug metabolism II. Analysis on relationship between enzyme activities of CYP2D6 and CYP2C19 and their relevant genotypes. Drug Metabolism and Pharmacokinetics. 2003, 18(1): 71-78.
[92] Shimizu T.,Ochiai H.,?sell F., et al. Bioinformatics research on inter-racial difference in drug metabolism I. Analysis on frequencies of mutant alleles and poor metabolizers on CYP2D6 and CYP2C19. Drug Metabolism and Pharmacokinetics. 2003, 18(1): 48-70.
[93] Zhou S.,Liu J.,Chowbay B. Polymorphism of human cytochrome P450 enzymes and its clinical impact. Drug metabolism reviews. 2009, 41(2): 89-295.
[94] Yue P.,Melamud E.,Moult J. SNPs 3 D: Candidate gene and SNP selection for association studies. BMC bioinformatics. 2006, 7(1): 166-180.
[95] Ferrer-Costa C.,Gelpi J.,Zamakola L., et al. PMUT: a web-based tool for the annotation of pathological mutations on proteins. Bioinformatics Applications Note. 2005, 21(14): 3176-3178.
[96] Stitziel N.,Binkowski T.,Tseng Y., et al. topoSNP: a topographic database of non-synonymous single nucleotide polymorphisms with and without known disease association. Nucleic Acids Research. 2004, 32(Database Issue): 520-522.
[97] Wang L.,Li Y.,Zhou S. A bioinformatics approach for the phenotype prediction of non-synonymous single nucleotide polymorphisms in human cytochrome P450s. Drug Metabolism and Disposition. 2009, 37(5): 977-991.
[98] Hodel E.,Ley S.,Qi W., et al. A microarray-based system for the simultaneous analysis of single nucleotide polymorphisms in human genes involved in the metabolism of anti-malarial drugs. Malaria Journal. 2009, 8(1): 285-294.
[99] Wen S.,Wang H.,Sun O., et al. Rapid detection of the known SNPs of CYP2C9 using oligonucleotide microarray. World Journal of Gastroenterology. 2003, 9(6): 1342-1346.
[100] Wen S.,Wang H.,Ding Y., et al. Screening of 12 SNPs of CYP3A4 in a Chinese population using oligonucleotide microarray. Genetic Testing. 2004, 8(4): 411-416.
[101] Rieder M.,Livingston R.,Stanaway I., et al. The environmental genome project: referencepolymorphisms for drug metabolism genes and genome-wide association studies. Drug metabolism reviews. 2008, 40(2): 241-261.
[102] de Leon J.,Susce M.,Johnson M., et al. DNA Microarray Technology in the Clinical Environment: The AmpliChip CYP450 Test for CYP2D6 and CYP2C19 Genotyping. CNS spectrums. 2009, 14(1): 19-34.
[103] Langenfeld E.,Meyer H.,Marcus K. Quantitative analysis of highly homologous proteins: the challenge of assaying the“CYP-ome”by mass spectrometry. Analytical and Bioanalytical Chemistry. 2008, 392(6): 1123-1134.
[104] Chen C. , Ma X. , Malfatti M., et al. A comprehensive investigation of 2-amino-1-methyl-6-phenylimidazo [4, 5-b] pyridine (PhIP) metabolism in the mouse using a multivariate data analysis approach. Chemical research in toxicology. 2007, 20(3): 531-542.
[105] Chen C.,Meng L.,Ma X., et al. Urinary metabolite profiling reveals CYP1A2-mediated metabolism of NSC686288 (aminoflavone). Journal of Pharmacology and Experimental Therapeutics. 2006, 318(3): 1330-1342.
[106] Crooke P.S.,Ritchie M.D.,Hachey D.L., et al. Estrogens, Enzyme Variants, and Breast Cancer: A Risk Model. Cancer Epidemiology Biomarkers & Prevention. 2006, 15(9): 1620-1629.
[107] Tang Z.,Martin M.,Guengerich F. Elucidation of Functions of Human Cytochrome P450 Enzymes: Identification of Endogenous Substrates in Tissue Extracts Using Metabolomic and Isotopic Labeling Approaches. Analytical Chemistry. 2009, 81(8): 3071-3078.
[1] Danielson P. The cytochrome P450 superfamily: biochemistry, evolution and drug metabolism in humans. Current Drug Metabolism. 2002, 3(6): 561-597.
[2] Hakkola J.,Tanaka E.,Pelkonen O. Developmental expression of cytochrome P450 enzymes in human liver. Pharmacology & toxicology. 1998, 82(5): 209-217.
[3] Wienkers L.C.,Heath T.G. Predicting in vivo drug interactions from in vitro drug discovery data. Nature Reviews Drug Discovery. 2005, 4(10): 825-833.
[4]刘端.细胞色素P450基因单核苷酸多态性对药物安全性影响评价体系的建立和应用[博士论文].西安:西北大学. 2010:
[5] Ingelman-Sundberg M. Polymorphism of cytochrome P450 and xenobiotic toxicity. Toxicology. 2002, 181447-452.
[6] Crawford D.C.,Akey D.T.,Nickerson D.A. The patterns of natural variation in human genes. Annual Review of Genomics and Human Genetics. 2005, 6(1): 287-312.
[7] Halushka M.K.,Fan J.B.,Bentley K., et al. Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis. Nature Genetics. 1999, 22(3): 239-247.
[8] Cargill M.,Altshuler D.,Ireland J., et al. Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nature Genetics. 1999, 22(3): 231-238.
[9] Sim S.C.,Miller W.L.,Zhong X.B., et al. Nomenclature for alleles of the cytochrome P450 oxidoreductase gene. Pharmacogenetics and genomics. 2009, 19(7): 565-566.
[10] Sim S.C.,Ingelman-Sundberg M. The Human Cytochrome P450 (CYP) Allele Nomenclature website: A peer-reviewed database of CYP variants and their associated effects. Human Genomics. 2010, 4(4): 278-281.
[11] Ingelman-Sundberg M.,Daly A.K.,Oscarson M., et al. Human cytochrome P450 (CYP) genes: recommendations for the nomenclature of alleles. Pharmacogenetics and genomics. 2000, 10(1): 91-93.
[12] Dahl M.L.,Bertilsson L.,Nordin C. Steady-state plasma levels of nortriptyline and its 10-hydroxy metabolite: relationship to theCYP2D6 genotype. Psychopharmacology. 1996, 123(4): 315-319.
[13] Fjordside L.,Jeppesen U.,Eap C., et al. The stereoselective metabolism of fluoxetine in poor and extensive metabolizers of sparteine. Pharmacogenetics and genomics. 1999, 9(1): 55-60.
[14] Crewe H.K.,Ellis S.W.,Lennard M.S., et al. Variable contribution of cytochromes p450 2d6, 2c9 and 3a4 to the 4-hydroxylation of tamoxifen by human liver microsomes* 1. Biochemical pharmacology. 1997, 53(2): 171-178.
[15] Takahashi H. , Echizen H. Pharmacogenetics of warfarin elimination and its clinical implications. Clinical pharmacokinetics. 2001, 40(8): 587-603.
[16] Varenhorst C.,James S.,Erlinge D., et al. Genetic variation of CYP2C19 affects both pharmacokinetic and pharmacodynamic responses to clopidogrel but not prasugrel in aspirin-treated patients with coronary artery disease. European heart journal. 2009, 30(14): 1744-1752.
[17] Brandt J.,Close S.,Iturria S., et al. Common polymorphisms of CYP2C19 and CYP2C9 affect the pharmacokinetic and pharmacodynamic response to clopidogrel but not prasugrel. Journal of Thrombosis and Haemostasis. 2007, 5(12): 2429-2436.
[18] Dai D.,Zeldin D.C.,Blaisdell J.A., et al. Polymorphisms in human CYP2C8 decrease metabolism of the anticancer drug paclitaxel and arachidonic acid. Pharmacogenetics and genomics. 2001, 11(7): 597-607.
[19] Rendic S. Summary of information on human CYP enzymes: human P450 metabolism data. Drug metabolism reviews. 2002, 34(1): 83-448.
[20] Nelson D.R. Introductory remarks on human CYPs. Drug metabolism reviews. 2002, 34(1-2): 1-5.
[21] Antony T.R.T.,Nagarajan S. DrugMetZ DB: an anthology of human drug metabolizing Chytochrome P450 enzymes. Bioinformation. 2006, 1(7): 248-250.
[22] Preissner S.,Kroll K.,Dunkel M., et al. SuperCYP: a comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions. Nucleic Acids Research. 2010, 38(suppl 1): 237-243.
[23] Lisitsa A.,Guseva S.,Karuzina I., et al. Cytochrome P450 database. SAR and QSAR in Environmental Research. 2001, 12(4): 359-366.
[24] Fischer M.,Knoll M.,Sirim D., et al. The Cytochrome P450 Engineering Database: a navigation and prediction tool for the cytochrome P450 protein family. Bioinformatics. 2007, 23(15): 2015-2017.
[25] Van der Weide J.,Steijns L.S.W. Cytochrome P450 enzyme system: genetic polymorphisms and impact on clinical pharmacology. Annals of clinical biochemistry. 1999, 36722-729.
[26] Jain K.K. Applications of AmpliChip CYP450. Molecular Diagnosis. 2005, 9(3): 119-127.
[27] van Schaik R.H.N. CYP450 pharmacogenetics for personalizing cancer therapy. Drug Resistance Updates. 2008, 11(3): 77-98.
[28] Ahn C. Pharmacogenomics in drug discovery and development. Genomics & Informatics. 2007, 5(2): 41-45.
[29] Kusama M.,Maeda K.,Chiba K., et al. Prediction of the effects of genetic polymorphism on the pharmacokinetics of CYP2C9 substrates from in vitro data. Pharmaceutical research. 2009, 26(4): 822-835.
[30] Dickinson G.L.,Rezaee S.,Proctor N.J., et al. Incorporating in vitro information on drug metabolism into clinical trial simulations to assess the effect of CYP2D6 polymorphism on pharmacokinetics and pharmacodynamics: dextromethorphan as a model application. The Journal of Clinical Pharmacology. 2007, 47(2): 175-186.
[31] Sirim D.,Wagner F.,Lisitsa A., et al. The Cytochrome P 450 Engineering Database: integration of biochemical properties. BMC biochemistry. 2009, 10(1): 27-30.
[1]莫莉,黄大毛,唐发清.分子动态模拟及其在生物大分子研究中的应用.生命的化学. 2007, 27(003): 243-245.
[2]陈敏伯.计算化学:从理论化学到分子模拟.北京:科学出版社. 2009: 51-60.
[3] Karplus M.,McCammon J.A. Molecular dynamics simulations of biomolecules. Nature Structural & Molecular Biology. 2002, 9(9): 646-652.
[4] Alder B.,Wainwright T. Studies in molecular dynamics. I. General method. The Journal of Chemical Physics. 1959, 31(459-467.
[5] Rahman A. Correlations in the motion of atoms in liquid argon. Phys. Rev. 1964, 136(2A): 405-411.
[6] Rahman A.,Stillinger F.H. Molecular dynamics study of liquid water. The Journal of Chemical Physics. 1971, 55(7): 3336-3359.
[7] McCammon J.A.,Gelin B.R.,Karplus M. Dynamics of folded proteins. Nature. 1977, 267(5612): 585-590.
[8] Ichiye T.,Karplus M. Fluorescence depolarization of tryptophan residues in proteins: a molecular dynamics study. Biochemistry. 1983, 22(12): 2884-2893.
[9] Levy R.M.,Karplus M.,Wolynes P.G. NMR relaxation parameters in molecules with internal motion: exact Langevin trajectory results compared with simplified relaxation models. Journal of the American Chemical Society. 1981, 103(20): 5998-6011.
[10] Olejniczak E.,Dobson C.,Karplus M., et al. Motional averaging of proton nuclear Overhauser effects in proteins. Predictions from a molecular dynamics simulation of lysozyme. Journal of the American Chemical Society. 1984, 106(7): 1923-1930.
[11] Cusack S.,Smith J.,Finney J., et al. Low frequency dynamics of proteins studied by neutron time-of-flight spectroscopy. Physica B+ C. 1986, 136(1-3): 256-259.
[12] Brünger A.,Brooks C.L.,Karplus M. Active site dynamics of ribonuclease. Proceedings of the National Academy of Sciences of the United States of America. 1985, 82(24): 8458-8462.
[13] Nadler W.,Brünger A.T.,Schulten K., et al. Molecular and stochastic dynamics of proteins. Proceedings of the National Academy of Sciences of the United States of America. 1987, 84(22): 7933-7937.
[14] Brünger A.T.,Kuriyan J.,Karplus M. Crystallographic R factor refinement by molecular dynamics. Science. 1987, 235(4787): 458-460.
[15] Brooks B.,Karplus M. Normal modes for specific motions of macromolecules: application to the hinge-bending mode of lysozyme. Proceedings of the National Academy of Sciences of the United States of America. 1985, 82(15): 4995-4999.
[16] Colonna-Cesari F.,Perahia D.,Karplus M., et al. Interdomain motion in liver alcohol dehydrogenase. Structural and energetic analysis of the hinge bending mode. Journal of Biological Chemistry. 1986, 261(32): 15273-15279.
[17] Harvey S.C.,Prabhakaran M.,Mao B., et al. Phenylalanine transfer RNA: molecular dynamics simulation. Science. 1984, 223(4641): 1189-1191.
[18] Case D.,Karplus M. Dynamics of ligand binding to heme proteins* 1. Journal of Molecular Biology. 1979, 132(3): 343-368.
[19] Brooks B.,Karplus M. Harmonic dynamics of proteins: normal modes and fluctuations in bovine pancreatic trypsin inhibitor. Proceedings of the National Academy of Sciences of the United States of America. 1983, 80(21): 6571-6575.
[20] Irikura K.,Tidor B.,Brooks B., et al. Transition from B to Z DNA: contribution of internal fluctuations to the configurational entropy difference. Science. 1985, 229(4713): 571-572.
[21] Karplus M. Molecular dynamics of biological macromolecules: A brief history and perspective. Biopolymers. 2003, 68(3): 350-358.
[22] Nakajima N.,Nakamura H.,Kidera A. Multicanonical ensemble generated by molecular dynamics simulation for enhanced conformational sampling of peptides. The Journal of Physical Chemistry B. 1997, 101(5): 817-824.
[23] Daggett V.,Kollman P.A.,Kuntz I.D. A molecular dynamics simulation of polyalanine: An analysis of equilibrium motions and helix–coil transitions. Biopolymers. 1991, 31(9): 1115-1134.
[24] van Gunsteren W.F.,Dolenc J.,Mark A.E. Molecular simulation as an aid to experimentalists. Current opinion in structural biology. 2008, 18(2): 149-153.
[25] Lindorff-Larsen K.,Best R.B.,DePristo M.A., et al. Simultaneous determination of protein structure and dynamics. Nature. 2005, 433(7022): 128-132.
[26] Faure P.,Micu A.,Perahia D., et al. Correlated intramolecular motions and diffuse x–ray scattering in lysozyme. Nature Structural & Molecular Biology. 1994, 1(2): 124-128.
[27] Wang W.,Donini O.,Reyes C.M., et al. Biomolecular simulations: recent developments inforce fields, simulations of enzyme catalysis, protein-ligand, protein-protein, and protein-nucleic acid noncovalent interactions. Annual Review of Biophysics and Biomolecular Structure. 2001, 30(1): 211-243.
[28] Carlson H.A.,McCammon J.A. Accommodating protein flexibility in computational drug design. Molecular Pharmacology. 2000, 57(2): 213-218.
[29] Kuwata K.,Matumoto T.,Cheng H., et al. NMR-detected hydrogen exchange and molecular dynamics simulations provide structural insight into fibril formation of prion protein fragment 106–126. Proceedings of the National Academy of Sciences of the United States of America. 2003, 100(25): 14790-14795.
[30] Xu Y.,Shen J.,Luo X., et al. Conformational transition of amyloidβ-peptide. Proceedings of the National Academy of Sciences of the United States of America. 2005, 102(15): 5403-5407.
[31] Tajkhorshid E.,Nollert P.,Jensen M., et al. Control of the selectivity of the aquaporin water channel family by global orientational tuning. Science. 2002, 296(5567): 525-530.
[32] Baker D. A surprising simplicity to protein folding. Nature. 2000, 405(6782): 39-42.
[33] Duan Y. , Kollman P.A. Pathways to a protein folding intermediate observed in a 1-microsecond simulation in aqueous solution. Science. 1998, 282(5389): 740-744.
[34] Scheraga H.A.,Khalili M.,Liwo A. Protein-folding dynamics: overview of molecular simulation techniques. Annual Review of Physical Chemistry. 2007, 58(1): 57-83.
[35] Lu H.,Schulten K. Steered molecular dynamics simulations of force‐ induced protein domain unfolding. Proteins: Structure, Function, and Bioinformatics. 1999, 35(4): 453-463.
[36] Liu S.,Fan S.,Sun Z. Structural and functional characterization of the human CCR5 receptor in complex with HIV gp120 envelope glycoprotein and CD4 receptor by molecular modeling studies. Journal of Molecular Modeling. 2003, 9(5): 329-336.
[37] Wlodawer A. , Vondrasek J. Inhibitors of HIV-1 protease: A Major Success of Structure-Assisted Drug Design 1. Annual Review of Biophysics and Biomolecular Structure. 1998, 27(1): 249-284.
[38] Perryman A.L.,Lin J.H.,McCammon J.A. HIV‐ 1 protease molecular dynamics of a wild‐ type and of the V82F/I84V mutant: Possible contributions to drug resistance and a potential new target site for drugs. Protein Science. 2004, 13(4): 1108-1123.
[39] Cheatham T.E. Simulation and modeling of nucleic acid structure, dynamics and interactions. Current opinion in structural biology. 2004, 14(3): 360-367.
[40] Song C.,Xia Y.,Zhao M., et al. The effect of salt concentration on DNA conformationtransition: a molecular-dynamics study. Journal of Molecular Modeling. 2006, 12(3): 249-254.
[41] Chang Y.T.,Loew G.H. Molecular dynamics simulations of P450 BM3--examination of substrate-induced conformational change. Journal of biomolecular structure & dynamics. 1999, 16(6): 1189-1203.
[42] Wade R.C.,Gabdoulline R.R.,Lüdemann S.K., et al. Electrostatic steering and ionic tethering in enzyme–ligand binding: Insights from simulations. Proceedings of the National Academy of Sciences of the United States of America. 1998, 95(11): 5942-5949.
[43] Bathelt C.,Schmid R.D.,Pleiss J. Regioselectivity of CYP2B6: homology modeling, molecular dynamics simulation, docking. Journal of Molecular Modeling. 2002, 8(11): 327-335.
[44] Venhorst J.,Ter Laak A.M.,Commandeur J.N.M., et al. Homology modeling of rat and human cytochrome P450 2D (CYP2D) isoforms and computational rationalization of experimental ligand-binding specificities. Journal of medicinal chemistry. 2003, 46(1): 74-86.
[45] Paulsen M.D.,Ornstein R.L. Dramatic differences in the motions of the mouth of open and closed cytochrome P450BM‐ 3 by molecular dynamics simulations. Proteins: Structure, Function, and Bioinformatics. 1995, 21(3): 237-243.
[46] Lüdemann S.K.,Carugo O.,Wade R.C. Substrate access to cytochrome P450cam: a comparison of a thermal motion pathway analysis with molecular dynamics simulation data. Journal of Molecular Modeling. 1997, 3(8): 369-374.
[47] Winn P.J.,Lüdemann S.K.,Gauges R., et al. Comparison of the dynamics of substrate access channels in three cytochrome P450s reveals different opening mechanisms and a novel functional role for a buried arginine. Proceedings of the National Academy of Sciences of the United States of America. 2002, 99(8): 5361-5366.
[48] Helms V.,Wade R.C. Thermodynamics of water mediating protein-ligand interactions in cytochrome P450cam: a molecular dynamics study. Biophysical journal. 1995, 69(3): 810-824.
[49] Helms V.,Wade R.C. Hydration energy landscape of the active site cavity in cytochrome P450cam. Proteins: Structure, Function, and Bioinformatics. 1998, 32(3): 381-396.
[50] Arnold G.E.,Ornstein R.L. Molecular dynamics study of time-correlated protein domain motions and molecular flexibility: cytochrome P450BM-3. Biophysical journal. 1997, 73(3): 1147-1159.
[51] Paulsen M.D. , Ornstein R.L. Binding free energy calculations for P450cam-substrate complexes. Protein engineering. 1996, 9(7): 567-571.
[52] Szklarz G.D.,Paulsen M.D. Molecular modeling of cytochrome P450 1A1: enzyme-substrate interactions and substrate binding affinities. Journal of Biomolecular Structure & Dynamics. 2002, 20(2): 155-162.
[53] Helms V.,Wade R.C. Computational alchemy to calculate absolute protein-ligand binding free energy. Journal of the American Chemical Society. 1998, 120(12): 2710-2713.
[54] KeserüG.M.,Kolossváry I.,Bertók B. Cytochrome P-450 catalyzed insecticide metabolism. Prediction of regio-and stereoselectivity in the primer metabolism of carbofuran: A theoretical study. Journal of the American Chemical Society. 1997, 119(22): 5126-5131.
[55] Harris D.L.,Loew G.H. Investigation of the proton-assisted pathway to formation of the catalytically active, ferryl species of P450s by molecular dynamics studies of P450eryF. Journal of the American Chemical Society. 1996, 118(27): 6377-6387.
[56] Park J.Y.,Harris D. Construction and assessment of models of CYP2E1: Predictions of metabolism from docking, molecular dynamics, and density functional theoretical calculations. Journal of Medicinal Chemistry. 2003, 46(9): 1645-1660.
[57] Harris D.,Loew G. Prediction of regiospecific hydroxylation of camphor analogs by cytochrome P450cam. Journal of the American Chemical Society. 1995, 117(10): 2738-2746.
[58] Fahmy A.,Wagner G. TreeDock: A tool for protein docking based on minimizing van der Waals energies. Journal of the American Chemical Society. 2002, 124(7): 1241-1250.
[59]段爱霞,陈晶,刘宏德, et al.分子对接方法的应用与发展.分析科学学报. 2009, 25(4):473-477.
[60] Meiler J. , Baker D. ROSETTALIGAND: Protein–small molecule docking with full side‐ chain flexibility. Proteins: Structure, Function, and Bioinformatics. 2006, 65(3): 538-548.
[61] Taylor R.D.,Jewsbury P.J.,Essex J.W. A review of protein-small molecule docking methods. Journal of computer-aided molecular design. 2002, 16(3): 151-166.
[62] Stoddard B.L.,Koshland D.E. Prediction of the structure of a receptor–protein complex using a binary docking method. Nature. 1992, 358(27): 774-776.
[63] Berchanski A.,Shapira B.,Eisenstein M. Hydrophobic complementarity in protein–protein docking. Proteins: Structure, Function, and Bioinformatics. 2004, 56(1): 130-142.
[64] Duhovny D.,Nussinov R.,Wolfson H. Efficient unbound docking of rigid molecules. Algorithms in Bioinformatics. 2002, 2452(185-200.
[65] Sun Y.,Ewing T.,Skillman A., et al. CombiDOCK: structure-based combinatorial docking andlibrary design. Journal of computer-aided molecular design. 1998, 12(6): 597-604.
[66] Oshiro C.M.,Kuntz I.D.,Dixon J.S. Flexible ligand docking using a genetic algorithm. Journal of computer-aided molecular design. 1995, 9(2): 113-130.
[67] Mangoni M.,Roccatano D.,Di Nola A. Docking of flexible ligands to flexible receptors in solution by molecular dynamics simulation. Proteins: Structure, Function, and Bioinformatics. 1999, 35(2): 153-162.
[68] Lybrand T.P. Ligand--protein docking and rational drug design. Current opinion in structural biology. 1995, 5(2): 224-228.
[69] Jenkins J.L.,Bender A.,Davies J.W. In silico target fishing: Predicting biological targets from chemical structure. Drug Discovery Today: Technologies. 2007, 3(4): 413-421.
[70] Hermann J.C.,Marti-Arbona R.,Fedorov A.A., et al. Structure-based activity prediction for an enzyme of unknown function. Nature. 2007, 448(7155): 775-779.
[71] Leach A.R.,Shoichet B.K.,Peishoff C.E. Prediction of protein-ligand interactions. Docking and scoring: successes and gaps. Journal of medicinal chemistry. 2006, 49(20): 5851-5855.
[72] de Graaf C.,Vermeulen N.P.E.,Feenstra K.A. Cytochrome P450 in silico: an integrative modeling approach. Journal of Medicinal Chemistry. 2005, 48(8): 2725-2755.
[73] de Groot M.J.,Ekins S. Pharmacophore modeling of cytochromes P450. Advanced drug delivery reviews. 2002, 54(3): 367-383.
[74] Hritz J.,de Ruiter A.,Oostenbrink C. Impact of plasticity and flexibility on docking results for cytochrome P450 2D6: a combined approach of molecular dynamics and ligand docking. Journal of medicinal chemistry. 2008, 51(23): 7469-7477.
[75] Kramer B.,Rarey M.,Lengauer T. Evaluation of the FLEXX incremental construction algorithm for protein–ligand docking. Proteins: Structure, Function, and Bioinformatics. 1999, 37(2): 228-241.
[76] Bissantz C.,Folkers G.,Rognan D. Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. Journal of Medicinal Chemistry. 2000, 43(25): 4759-4767.
[77] Poornima C.,Dean P. Hydration in drug design. 1. Multiple hydrogen-bonding features of water molecules in mediating protein-ligand interactions. Journal of Computer-Aided Molecular Design. 1995, 9(6): 500-512.
[78] Wester M.R.,Johnson E.F.,Marques-Soares C., et al. Structure of a substrate complex of mammalian cytochrome P450 2C5 at 2.3 resolution: evidence for multiple substrate bindingmodes. Biochemistry. 2003, 42(21): 6370-6379.
[79] Williams P.A.,Cosme J.,Ward A., et al. Crystal structure of human cytochrome P450 2C9 with bound warfarin. Nature. 2003, 424(6947): 464-468.
[80] Wester M.R.,Yano J.K.,Schoch G.A., et al. The structure of human cytochrome P450 2C9 complexed with flurbiprofen at 2.0- resolution. Journal of Biological Chemistry. 2004, 279(34): 35630-35637.
[81] de Graaf C.,Pospisil P.,Pos W., et al. Binding mode prediction of cytochrome p450 and thymidine kinase protein-ligand complexes by consideration of water and rescoring in automated docking. Journal of medicinal chemistry. 2005, 48(7): 2308-2318.
[82] Keser G.M. A virtual high throughput screen for high affinity cytochrome P450cam substrates. Implications for in silico prediction of drug metabolism. Journal of Computer-Aided Molecular Design. 2001, 15(7): 649-657.
[83] De Voss J.J.,Sibbesen O.,Zhang Z., et al. Substrate docking algorithms and prediction of the substrate specificity of cytochrome P450cam and its L244A mutant. Journal of the American Chemical Society. 1997, 119(24): 5489-5498.
[84] Verras A.,Kuntz I.D.,de Montellano P.R.O. Computer-assisted design of selective imidazole inhibitors for cytochrome p450 enzymes. Journal of Medicinal Chemistry. 2004, 47(14): 3572-3579.
[85] García A.E. Large-amplitude nonlinear motions in proteins. Physical Review Letters. 1992, 68(17): 2696-2699.
[86] Amadei A.,Linssen A.B.M.,Berendsen H.J.C. Essential dynamics of proteins. Proteins: Structure Function and Genetics. 1993, 17(412-425.
[87] Grubmüller H. Predicting slow structural transitions in macromolecular systems: Conformational flooding. Physical Review E. 1995, 52(3): 2893-2906.
[88] Hayward S.,de Groot B.L. Normal modes and essential dynamics. Methods in Molecular Biology. 2008, 443(1): 89-106.
[89] Van Aalten D.,De Groot B.,Findlay J., et al. A comparison of techniques for calculating protein essential dynamics. Journal of computational chemistry. 1997, 18(2): 169-181.
[90] Van Aalten D.,Conn D.,De Groot B., et al. Protein dynamics derived from clusters of crystal structures. Biophysical journal. 1997, 73(6): 2891-2896.
[91] De Groot B.,Hayward S.,Van Aalten D., et al. Domain motions in bacteriophage T 4 lysozyme: A comparison between molecular dynamics and crystallographic data. ProteinsStructure Function and Genetics. 1998, 31(2): 116-127.
[92] Qian B.,Ortiz A.R.,Baker D. Improvement of comparative model accuracy by free-energy optimization along principal components of natural structural variation. Proceedings of the National Academy of Sciences of the United States of America. 2004, 101(43): 15346-15351.
[93] Nebert D.,Russell D. Clinical importance of the cytochromes P450. The Lancet. 2002, 360(9340): 1155-1162.
[94] Hodgson J. ADMET-turning chemicals into drugs. Nature Biotechnology. 2001, 19(8): 722-726.
[95] Lewis D.F.V. Human cytochromes P450 associated with the phase 1 metabolism of drugs and other xenobiotics: a compilation of substrates and inhibitors of the CYP1, CYP2 and CYP3 families. Current medicinal chemistry. 2003, 10(19): 1955-1972.
[96] Ingelman-Sundberg M.,Sim S.C. , Gomez A., et al. Influence of cytochrome P450 polymorphisms on drug therapies: pharmacogenetic, pharmacoepigenetic and clinical aspects. Pharmacology & therapeutics. 2007, 116(3): 496-526.
[97] Daly A.K. Pharmacogenetics of the cytochromes P450. Current Topics in Medicinal Chemistry. 2004, 4(16): 1733-1744.
[98] Ding X.,Kaminsky L. Human extrahepatic cytochromes P450: function in xenobiotic metabolism and tissue-selective chemical toxicity in the respiratory and gastrointestinal tracts. Annual review of pharmacology and toxicology. 2003, 43(149-173.
[99] Wang B.,Zhou S.F. Synthetic and natural compounds that interact with human cytochrome P450 1A2 and implications in drug development. Current medicinal chemistry. 2009, 16(31): 4066-4218.
[100] Sansen S.,Yano J.,Reynald R., et al. Adaptations for the oxidation of polycyclic aromatic hydrocarbons exhibited by the structure of human P450 1A2. Journal of Biological Chemistry. 2007, 282(19): 14348-14355.
[101] Cojocaru V.,Winn P.,Wade R. The ins and outs of cytochrome P450s. Biochimica et Biophysica Acta. 2007, 1770(3): 390-401.
[102] Yaffe E.,Fishelovitch D.,Wolfson H.J., et al. MolAxis: Efficient and accurate identification of channels in macromolecules. Proteins: Structure, Function, and Bioinformatics. 2008, 73(1): 72-86.
[103] Behera R.,Mazumdar S. Roles of two surface residues near the access channel in the substrate recognition by cytochrome P450cam. Biophysical chemistry. 2008, 135(1-3): 1-6.
[104] Bechtel S.,Belkina N.,Bernhardt R. The effect of amino‐ acid substitutions I112P, D147E and K152N in CYP11B2 on the catalytic activities of the enzyme. European Journal of Biochemistry. 2002, 269(4): 1118-1127.
[105] Scott E.,He Y.,Halpert J. Substrate Routes to the Buried Active Site May Vary among Cytochromes P450: Mutagenesis of the F- G Region in P450 2B1. Chemical Research in Toxicology. 2002, 15(11): 1407-1413.
[106] Fishelovitch D.,Shaik S.,Wolfson H., et al. How Does the Reductase Help To Regulate the Catalytic Cycle of Cytochrome P450 3A4 Using the Conserved Water Channel? The Journal of Physical Chemistry B. 2010, 114(17): 5964-5970.
[107] Winn P.,Lüdemann S.,Gauges R., et al. Comparison of the dynamics of substrate access channels in three cytochrome P450s reveals different opening mechanisms and a novel functional role for a buried arginine. Proceedings of the National Academy of Sciences of the United States of America. 2002, 99(8): 5361-5366.
[108] Fishelovitch D.,Shaik S.,Wolfson H., et al. Theoretical Characterization of Substrate Access/Exit Channels in the Human Cytochrome P450 3A4 Enzyme: Involvement of Phenylalanine Residues in the Gating Mechanism. The Journal of Physical Chemistry B. 2009, 113(39): 13018-13025.
[109] Wen Z.,Baudry J.,Berenbaum M., et al. Ile115Leu mutation in the SRS1 region of an insect cytochrome P450 (CYP6B1) compromises substrate turnover via changes in a predicted product release channel. Protein Engineering Design and Selection. 2005, 18(4): 191-199.
[110] Zhou H.,Josephy P.,Kim D., et al. Functional characterization of four allelic variants of human cytochrome P450 1A2. Archives of biochemistry and biophysics. 2004, 422(1): 23-30.
[111] Saito Y.,Hanioka N.,Maekawa K., et al. Functional analysis of three CYP1A2 variants found in a Japanese population. Drug Metabolism and Disposition. 2005, 33(12): 1905-1910.
[112] Murayama N.,Soyama A.,Saito Y., et al. Six novel nonsynonymous CYP1A2 gene polymorphisms: catalytic activities of the naturally occurring variant enzymes. Journal of Pharmacology and Experimental Therapeutics. 2004, 308(1): 300-306.
[113] Laskowski R.,Gerick F.,Thornton J. The structural basis of allosteric regulation in proteins. FEBS letters. 2009, 583(11): 1692-1698.
[114] Tsai C.,del Sol A.,Nussinov R. Allostery: absence of a change in shape does not imply that allostery is not at play. Journal of molecular biology. 2008, 378(1): 1-11.
[115] Goodey N.,Benkovic S. Allosteric regulation and catalysis emerge via a common route.Nature Chemical Biology. 2008, 4(8): 474-482.
[116] Ackers G.,Smith F. Effects of site-specific amino acid modification on protein interactions and biological function. Annual Review of Biochemistry. 1985, 54(1): 597-629.
[117] Tousignant A.,Pelletier J. Protein motions promote catalysis. Chemistry & biology. 2004, 11(8): 1037-1042.
[118] Lewis D.,Lake B.,George S., et al. Molecular modelling of CYP1 family enzymes CYP1A1, CYP1A2, CYP1A6 and CYP1B1 based on sequence homology with CYP102. Toxicology. 1999, 139(1-2): 53-79.
[119] Kabsch W.,Sander C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 1983, 22(12): 2577-2637.
[120] Mongan J. Interactive essential dynamics. Journal of Computer-Aided Molecular Design. 2004, 18(6): 433-436.
[121] Humphrey W.,Dalke A.,Schulten K. VMD: visual molecular dynamics. Journal of Molecular Graphics. 1996, 14(1): 33-38.
[122] Hubbard S.,Thornton J. NACCESS computer program. Department of Biochemistry and Molecular Biology, University College London. 1993,
[123] Liang J.,Edelsbrunner H.,Woodward C. Anatomy of protein pockets and cavities: measurement of binding site geometry and implications for ligand design. Protein Science. 1998, 7(1884-1897.
[124] Pet ek M.,Otyepka M.,BanáP., et al. CAVER: a new tool to explore routes from protein clefts, pockets and cavities. BMC bioinformatics. 2006, 7(1): 316-324.
[125] DeLano W. The case for open-source software in drug discovery. Drug Discovery Today. 2005, 10(3): 213-217.
[126] Morris G.,Goodsell D.,Halliday R., et al. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry. 1998, 19(14): 1639-1662.
[127] Totrov M.,Abagyan R. Flexible ligand docking to multiple receptor conformations: a practical alternative. Current opinion in structural biology. 2008, 18(2): 178-184.
[128] Lin J.,Perryman A.,Schames J., et al. Computational drug design accommodating receptor flexibility: the relaxed complex scheme. Journal of the American Chemical Society. 2002, 124(20): 5632-5633.
[129] Thompson J.,Gibson T.,Plewniak F., et al. The CLUSTAL_X windows interface: flexiblestrategies for multiple sequence alignment aided by quality analysis tools. Nucleic acids research. 1997, 25(24): 4876-4882.
[130] Gouet P.,Courcelle E.,Stuart D. ESPript: analysis of multiple sequence alignments in PostScript. Bioinformatics. 1999, 15(4): 305-308.
[131] Achary M.,Nagarajaram H. Effects of disease causing mutations on the essential motions in proteins. Journal of biomolecular structure & dynamics. 2009, 26(5): 609-624.
[132] Daily M.,Gray J. Local motions in a benchmark of allosteric proteins. Proteins: Structure, Function, and Bioinformatics. 2007, 67(2): 385-399.
[133] Rydberg P.,Rod T.,Olsen L., et al. Dynamics of water molecules in the active-site cavity of human cytochromes P450. The Journal of Physical Chemistry. B. 2007, 111(19): 5445-5457.
[134] Lee Y.,Wilson R.,Rupniewski I., et al. P450cam Visits an Open Conformation in the Absence of Substrate. Biochemistry. 2010, 49(16): 3412-3419.
[135] Bauer E.,Guo Z.,Ueng Y., et al. Oxidation of benzo pyrene by recombinant human cytochrome P450 enzymes. Chemical Research in Toxicology. 1995, 8(1): 136-142.
[136] Zhou S.,Yang L.,Zhou Z., et al. Insights into the substrate specificity, inhibitors, regulation, and polymorphisms and the clinical impact of human cytochrome P450 1A2. The AAPS journal. 2009, 11(3): 481-494.
[137] Puchkaev A.V.,Koo L.S.,Ortiz de Montellano P.R. Aromatic stacking as a determinant of the thermal stability of CYP119 from Sulfolobus solfataricus. Archives of Biochemistry and Biophysics. 2003, 409(1): 52-58.
[138] Cui Q.,Karplus M. Allostery and cooperativity revisited. Protein Science. 2008, 17(8): 1295-1307.
[139] del Sol A.,Tsai C.,Ma B., et al. The origin of allosteric functional modulation: multiple pre-existing pathways. Structure. 2009, 17(8): 1042-1050.
[1] Mitchell T.M. Machine learning and data mining. Communications of the ACM. 1999, 42(11): 30-36.
[2] Bishop C.M. Pattern recognition and machine learning. New York: Springer 2006: 7.
[3]陈凯,朱钰.机器学习及其相关算法综述.统计与信息论坛. 2007, 22(005): 105-112.
[4] Kotsiantis S.,Zaharakis I.,Pintelas P. Machine learning: a review of classification and combining techniques. Artificial Intelligence Review. 2006, 26(3): 159-190.
[5] Barlow H.B. Unsupervised learning. Neural Computation. 1989, 1(3): 295-311.
[6] Love B.C. Comparing supervised and unsupervised category learning. Psychonomic Bulletin & Review. 2002, 9(4): 829-835.
[7] Board R.,Pitt L. Semi-supervised learning. Machine Learning. 1989, 4(1): 41-65.
[8] Chapelle O.,Scholkopf B.,Zien A. Semi-supervised learning. London: The MIT Press. 2006: 1-8.
[9] Tan A.C.,Naiman D.Q.,Xu L., et al. Simple decision rules for classifying human cancers from gene expression profiles. Bioinformatics. 2005, 21(20): 3896-3904.
[10] Selbig J.,Mevissen T.,Lengauer T. Decision tree-based formation of consensus protein secondary structure prediction. Bioinformatics. 1999, 15(12): 1039-1046.
[11] Barlow T.,Neville P., Case study: visualization for decision tree analysis in data mining,in. 2001: Published by the IEEE Computer Society.
[12] Mitchell T.M. Machine learning. New York: McGraw Hill. 1997: 52-78.
[13] Takimoto E.,Maruoka A. Top-down decision tree learning as information based boosting. Theoretical Computer Science. 2003, 292(2): 447-464.
[14] Muharram M.A.,Smith G.D. Evolutionary feature construction using information gain and gini index. Genetic Programming. 2004, 379-388.
[15] Quinlan J.R. Induction of decision trees. Machine Learning. 1986, 1(1): 81-106.
[16] Wang J.,Cui J.,Zhao K. Investigation on AQ11, ID3 and the principle of discernibility matrix. Journal of Computer Science and Technology. 2001, 16(1): 1-12.
[17] Markou M.,Singh S. Novelty detection: a review--part 2::: neural network based approaches. Signal Processing. 2003, 83(12): 2499-2521.
[18] KurkováV. Kolmogorov's theorem and multilayer neural networks. Neural Networks. 1992, 5(3): 501-506.
[19]阎平凡,张长水.人工神经网络与模拟进化计算.北京:清华大学出版社. 2000: 60-96.
[20]郭秀娟.数据挖掘方法综述.吉林建筑工程学院学报. 2004, 21(1): 49-53.
[21] Ilonen J.,Kamarainen J.K.,Lampinen J. Differential evolution training algorithm for feed-forward neural networks. Neural Processing Letters. 2003, 17(1): 93-105.
[22] Rumelhart D.E.,Hintont G.E.,Williams R.J. Learning representations by back-propagating errors. Nature. 1986, 323(6088): 533-536.
[23]李翱翔,陈健. BP神经网络参数改进方法综述.数字通信世界. 2009, (001): 62-64.
[24] Kawato M. Feedback-error-learning neural network for supervised motor learning. Advanced neural computers. 1990, 6(3): 365-372.
[25] Kohonen T. The self-organizing map. Proceedings of the IEEE. 1990, 78(9): 1464-1480.
[26]涂晓芝,颜学峰,钱锋.自组织映射网络及其在化学化工领域中的应用进展.计算与应用化学. 2005, 22(9): 737-744.
[27] Holland J.H. Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press. 1975:
[28] rey Horn J.,Nafpliotis N.,Goldberg D.E. Multiobjective optimization using the niched pareto genetic algorithm. Urbana. 1993, 5161801-2996.
[29] Whitley D. A genetic algorithm tutorial. Statistics and computing. 1994, 4(2): 65-85.
[30] Manderick B.,de Weger M.,Spiessens P., The genetic algorithm and the structure of the fitness landscape,in. 1991: Morgan Kaufmann Publishers.
[31]王小平,曹立明.遗传算法:理论,应用及软件实现.西安:西安交通大学出版社. 2002: 18-50.
[32]陈有青,徐蔡星,钟文亮, et al.一种改进选择算子的遗传算法.计算机工程与应用. 2008, 44(2): 44-50.
[33] Goldberg D.E.,Deb K. A comparative analysis of selection schemes used in genetic algorithms. Foundations of genetic algorithms. 1991, 169-93.
[34] Poon P.W.,Carter J.N. Genetic algorithm crossover operators for ordering applications. Computers & Operations Research. 1995, 22(1): 135-147.
[35] Srinivas M.,Patnaik L.M. Adaptive probabilities of crossover and mutation in genetic algorithms. Systems, Man and Cybernetics, IEEE Transactions on. 1994, 24(4): 656-667.
[36] Baranczewski P.,Stanczak A.,Sundberg K., et al. Introduction to in vitro estimation ofmetabolic stability and drug interactions of new chemical entities in drug discovery and development. Pharmacol Rep. 2006, 58(4): 453-472.
[37] Burton J.,Ijjaali I.,Petitet F., et al. Virtual screening for cytochromes P450: successes of machine learning filters. Combinatorial Chemistry &# 38; High Throughput Screening. 2009, 12(4): 369-382.
[38] Sun H.,Scott D.O. Structure‐ based Drug Metabolism Predictions for Drug Design. Chemical Biology & Drug Design. 2010, 75(1): 3-17.
[39] Madden J.C.,Cronin M.T.D. Structure-based methods for the prediction of drug metabolism. Expert Opinion on Drug Metabolism & Toxicology. 2006, 2(4): 545-557.
[40] Fox T.,Kriegl J.M. Machine learning techniques for in silico modeling of drug metabolism. Current Topics in Medicinal Chemistry. 2006, 6(15): 1579-1591.
[41] Korolev D.,Balakin K.V.,Nikolsky Y., et al. Modeling of human cytochrome P450-mediated drug metabolism using unsupervised machine learning approach. Journal of medicinal chemistry. 2003, 46(17): 3631-3643.
[42] Zhang H.,Singer B. Recursive partitioning in the health sciences. New York: Springer Verlag. 1999: 7-16.
[43] Feng J.,Lurati L.,Ouyang H., et al. Predictive toxicology: benchmarking molecular descriptors and statistical methods. Journal of chemical information and computer sciences. 2003, 43(5): 1463-1470.
[44] Rusinko III A.,Farmen M.W.,Lambert C.G., et al. Analysis of a Large Structure/Biological Activity Data Set Using Recursive Partitioning 1. Journal of chemical information and computer sciences. 1999, 39(6): 1017-1026.
[45] van Rhee A.M.,Stocker J.,Printzenhoff D., et al. Retrospective analysis of an experimental high-throughput screening data set by recursive partitioning. Journal of Combinatorial Chemistry. 2001, 3(3): 267-277.
[46] Ekins S.,Berbaum J.,Harrison R.K. Generation and validation of rapid computational filters for CYP2D6 and CYP3A4. Drug metabolism and disposition. 2003, 31(9): 1077-1080.
[47] Ekins S. In silico approaches to predicting drug metabolism, toxicology and beyond. Biochemical Society Transactions. 2003, 31(3): 611-614.
[48] Dixon S.L.,Villar H.O. Investigation of classification methods for the prediction of activity in diverse chemical libraries. Journal of computer-aided molecular design. 1999, 13(5): 533-545.
[49] Susnow R.G.,Dixon S.L. Use of robust classification techniques for the prediction of humancytochrome P450 2D6 inhibition. Journal of chemical information and computer sciences. 2003, 43(4): 1308-1315.
[50] Hudelson M.G.,Jones J.P. Line-walking method for predicting the inhibition of p450 drug metabolism. Journal of medicinal chemistry. 2006, 49(14): 4367-4373.
[51] Yap C.W.,Chen Y.Z. Prediction of cytochrome P450 3A4, 2D6, and 2C9 inhibitors and substrates by using support vector machines. Journal of chemical information and modeling. 2005, 45(4): 982-992.
[52] Burton J.,Ijjaali I.,Barberan O., et al. Recursive partitioning for the prediction of cytochromes P450 2D6 and 1A2 inhibition: importance of the quality of the dataset. Journal of medicinal chemistry. 2006, 49(21): 6231-6240.
[53] Chohan K.K.,Paine S.W.,Mistry J., et al. A rapid computational filter for cytochrome P450 1A2 inhibition potential of compound libraries. Journal of medicinal chemistry. 2005, 48(16): 5154-5161.
[54] Arimoto R.,Prasad M.A.,Gifford E.M. Development of CYP3A4 inhibition models: comparisons of machine-learning techniques and molecular descriptors. Journal of biomolecular screening. 2005, 10(3): 197-205.
[55] Zupan J.,Gasteiger J. Neural networks in chemistry and drug design. Weinheim: Vch Verlagsgesellschaft Mbh. 1999: 157-172.
[56] Maniyar D.M.,Nabney I.T.,Williams B.S., et al. Data visualization during the early stages of drug discovery. Journal of chemical information and modeling. 2006, 46(4): 1806-1818.
[57] Burden F.R.,Winkler D.A.,Polley M.J. Predictive human intestinal absorption QSAR models using Bayesian regularized neural networks. Australian journal of chemistry. 2005, 58(12): 859-863.
[58] Winkler D.A. Neural networks as robust tools in drug lead discovery and development. Molecular biotechnology. 2004, 27(2): 139-167.
[59] Molnár L.,Keser G.M. A neural network based virtual screening of cytochrome P450 3A4 inhibitors. Bioorganic & medicinal chemistry letters. 2002, 12(3): 419-421.
[60] Balakin K.V.,Ekins S.,Bugrim A., et al. Kohonen maps for prediction of binding to human cytochrome P450 3A4. Drug metabolism and disposition. 2004, 32(10): 1183-1189.
[61] Sean E.O.B.,de Groot M.J. Greater than the sum of its parts: combining models for useful ADMET prediction. Journal of medicinal chemistry. 2005, 48(4): 1287-1291.
[62] Wang Y.H.,Li Y.,Li Y.H., et al. Modeling Km values using electrotopological state: substratesfor cytochrome P450 3A4-mediated metabolism. Bioorganic & medicinal chemistry letters. 2005, 15(18): 4076-4084.
[63] Lewis D.F.V. 57 varieties: the human cytochromes P450. Parmacogenomics. 2004, 5(3): 305-318.
[64] Feiters M.C.,Rowan A.E.,Nolte R.J.M. From simple to supramolecular cytochrome P450 mimics. Chemical Society Reviews. 2000, 29(6): 375-384.
[65] Nelson D.R.,Kamataki T.,Waxman D.J., et al. The P450 superfamily: update on new sequences, gene mapping, accession numbers, early trivial names of enzymes, and nomenclature. DNA and Cell Biology. 1993, 12(1): 1-51.
[66] Nelson D.R. Cytochrome P450 Nomenclature, 2004. Methods in Molecular Biology 2006, 3201-10.
[67] Lewis D.F.V.,Ito Y. Cytochrome P450 Structure and Function: An Evolutionary Perspective. Cambridge, UK.: Royal Society of Chemistry. 2008: 4-39.
[68] Guengerich F.P. Cytochromes P450, drugs, and diseases. Molecular Interventions. 2003, 3(4): 194-204.
[69] Evans W.E.,Relling M.V. Pharmacogenomics: translating functional genomics into rational therapeutics. Science. 1999, 286(5439): 487-491.
[70] Patterson L.H. , Murray G.I. Tumour cytochrome P450 and drug activation. Current pharmaceutical design. 2002, 8(15): 1335-1347.
[71] Brown C.M.,Reisfeld B.,Mayeno A.N. Cytochromes P450: a structure-based summary of biotransformations using representative substrates. Drug metabolism reviews. 2008, 40(1): 1-100.
[72] Veith H.,Southall N.,Huang R., et al. Comprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries. Nature biotechnology. 2009, 27(11): 1050-1055.
[73] Lewis D.F.V. Molecular modeling of human cytochrome P450-substrate interactions. Drug metabolism reviews. 2002, 34(1-2): 55-67.
[74] Ito Y.,Kondo H.,Goldfarb P.S., et al. Analysis of CYP2D6 substrate interactions by computational methods. Journal of Molecular Graphics and Modelling. 2008, 26(6): 947-956.
[75] Park H.,Lee S.,Suh J. Structural and dynamical basis of broad substrate specificity, catalytic mechanism, and inhibition of cytochrome P450 3A4. J. Am. Chem. Soc. 2005, 127(39): 13634-13642.
[76] Seifert A.,Tatzel S.,Schmid R.D., et al. Multiple molecular dynamics simulations of humanp450 monooxygenase CYP2C9: the molecular basis of substrate binding and regioselectivity toward warfarin. Proteins: Structure, Function, and Bioinformatics. 2006, 64(1): 147-155.
[77] Ekins S.,de Groot M.J.,Jones J.P. Pharmacophore and three-dimensional quantitative structure activity relationship methods for modeling cytochrome P450 active sites. Drug metabolism and disposition. 2001, 29(7): 936-944.
[78] de Groot M.J.,Ekins S. Pharmacophore modeling of cytochromes P450. Advanced drug delivery reviews. 2002, 54(3): 367-383.
[79] Ekins S.,Stresser D.M.,Andrew Williams J. In vitro and pharmacophore insights into CYP3A enzymes. Trends in pharmacological sciences. 2003, 24(4): 161-166.
[80] Friesner R.A. , Guallar V. Ab initio quantum chemical and mixed quantum mechanics/molecular mechanics (QM/MM) methods for studying enzymatic catalysis. Physical Chemistry. 2005, 56(1): 389-427.
[81] Bathelt C.M.,Zurek J.,Mulholland A.J., et al. Electronic structure of compound I in human isoforms of cytochrome P450 from QM/MM modeling. J. Am. Chem. Soc. 2005, 127(37): 12900-12908.
[82] Crivori P.,Poggesi I. Computational approaches predicting CYP-related metabolism properties in the screening of new drugs. European journal of medicinal chemistry. 2006, 41(7): 795-808.
[83] Xie Z.,Zhang T.,Wang J.F., et al. The computational model to predict accurately inhibitory activity for inhibitors towardsCYP3A4. Computers in Biology and Medicine. 2010, 40(11-12): 845-852.
[84] Michielan L.,Terfloth L.,Gasteiger J., et al. Comparison of Multilabel and Single-Label Classification Applied to the Prediction of the Isoform Specificity of Cytochrome P450 Substrates. Journal of chemical information and modeling. 2009, 49(11): 2588-2605.
[85] Guengerich F.P. Cytochrome P-450 3A4: regulation and role in drug metabolism. Annual review of pharmacology and toxicology. 1999, 391-17.
[86] Wishart D.S.,Knox C.,Guo A.C., et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic acids research. 2008, 36(suppl 1): D901-D906.
[87] Halgren T.A. Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry. 1996, 17(5-6): 490-519.
[88] Stewart J.J.P. MOPAC: a semiempirical molecular orbital program. Journal of Computer-Aided Molecular Design. 1990, 4(1): 1-103.
[89] Pallas (version 1.2 for Windows) distributed by Compu Drug Chemistry Ltd.
[90] Frank E.,Hall M.,Trigg L., et al. Data mining in bioinformatics using Weka. Bioinformatics. 2004, 20(15): 2479-2481.
[91] Witten I.H.,Frank E. Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann Pub. 2005:
[92] Guyon I.,Elisseeff A. An introduction to variable and feature selection. The Journal of Machine Learning Research. 2003, 31157-1182.
[93] Ou G.,Murphey Y.L. Multi-class pattern classification using neural networks. Pattern Recognition. 2007, 40(1): 4-18.
[94] Hirose Y.,Yamashita K.,Hijiya S. Back-propagation algorithm which varies the number of hidden units. Neural Networks. 1991, 4(1): 61-66.
[95] Zhang M.L.,Zhou Z.H., A k-nearest neighbor based algorithm for multi-label classification,in. 2005: IEEE.
[96] Gersmann K.,Hammer B. Improving iterative repair strategies for scheduling with the SVM. Neurocomputing. 2005, 63271-292.
[97] Hristozov D.,Gasteiger J.,Da Costa F.B. Multilabeled classification approach to find a plant source for terpenoids. J. Chem. Inf. Model. 2008, 48(1): 56-67.
[98] Safavian S.R.,Landgrebe D. A survey of decision tree classifier methodology. Systems, Man and Cybernetics, IEEE Transactions on. 2002, 21(3): 660-674.
[99] Zhao Y.,Zhang Y. Comparison of decision tree methods for finding active objects. Advances in Space Research. 2008, 41(12): 1955-1959.
[100] Williams P.A.,Cosme J.,Ward A., et al. Crystal structure of human cytochrome P450 2C9 with bound warfarin. Nature. 2003, 424(6497): 464-468.
[101] Williams P.A.,Cosme J.,Vinkovic D.M., et al. Crystal structures of human cytochrome P450 3A4 bound to metyrapone and progesterone. Science. 2004, 305(5684): 683-686.
[102] Sevrioukova I.F.,Poulos T.L. Structure and mechanism of the complex between cytochrome P4503A4 and ritonavir. Proceedings of the National Academy of Sciences. 2010, 107(43): 18422-18427.
[103] Sansen S.,Yano J.K.,Reynald R.L., et al. Adaptations for the oxidation of polycyclic aromatic hydrocarbons exhibited by the structure of human P450 1A2. Journal of Biological Chemistry. 2007, 282(19): 14348-14355.
[104] Tsoumakas G.,Katakis I. Multi-label classification: An overview. International Journal of Data Warehousing and Mining. 2007, 3(3): 1-13.
[105] McCallum A.K., Multi-label text classification with a mixture model trained by EM,in AAAI99 Workshop on Text Learing. 1999: Citeseer.
[106] Boutell M.R.,Luo J.,Shen X., et al. Learning multi-label scene classification. Pattern Recognition. 2004, 37(9): 1757-1771.
[107] Diplaris S.,Tsoumakas G.,Mitkas P., et al. Protein classification with multiple algorithms. Advances in Informatics. 2005, 3746448-456.
[108] Clare A.,King R. Predicting gene function in Saccharomyces cerevisiae. Bioinformatics. 2003, 19(suppl 2): 42-49.
[1]安丽英,相玉红,张卓勇, et al.定量构效关系研究进展及其应用.首都师范大学学报:自然科学版. 2006, 27(3): 52-57.
[2] Martin B.R. Cellular effects of cannabinoids. Pharmacological Reviews. 1986, 38(1): 45-74.
[3] Hansch C.,Muir R.M.,Fujita T., et al. The correlation of biological activity of plant growth regulators and chloromycetin derivatives with Hammett constants and partition coefficients. Journal of the American Chemical Society. 1963, 85(18): 2817-2824.
[4] Hansch C. Quantitative structure-activity relationships in drug design. New York: Academic Press. 1971:
[5]于瑞莲,胡恭任.环境化学中有机化合物毒性的QSAR研究方法.环境科学与技术. 2003, 26(1): 57-59.
[6] Yang G.F.,Huang X. Development of quantitative structure-activity relationships and its application in rational drug design. Current Pharmaceutical Design. 2006, 12(35): 4601-4611.
[7] Kubinyi H. QSAR: Hansch analysis and related approaches. New York: VCH Publisher. 1993: 57-85.
[8] Marshall G.R. Computer-aided drug design. Annual Review of Pharmacology and Toxicology. 1987, 27(1): 193-213.
[9] Topliss J.G. A manual method for applying the Hansch approach to drug design. Journal of Medicinal Chemistry. 1977, 20(4): 463-469.
[10] Free S.M.,Wilson J.W. A mathematical contribution to structure-activity studies. Journal of Medicinal Chemistry. 1964, 7(4): 395-399.
[11] Valkenburg W.V. Biological Correlations-The Hansch Approach. Washington D.C American Chemical Society. 1975: 115-129.
[12] Kier L.B.,Hall L.H. Intermolecular accessibility: the meaning of molecular connectivity. Journal of Chemical Information and Computer Sciences. 2000, 40(3): 792-795.
[13] Sanz F.,López de Brias E.,Rodríguez J., et al. Theoretical Study on the Metabolism of Caffeine by Cytochrome P‐ 450 1A2 and its Inhibition. Quantitative Structure‐ Activity Relationships. 1994, 13(3): 281-284.
[14] Fuhr U.,Strobl G.,Manaut F., et al. Quinolone antibacterial agents: relationship betweenstructure and in vitro inhibition of the human cytochrome P450 isoform CYP1A2. Molecular Pharmacology. 1993, 43(2): 191-199.
[15] Lee H.,Yeom H.,Kim Y.G., et al. Structure-related inhibition of human hepatic caffeine N3-demethylation by naturally occurring flavonoids. Biochemical Pharmacology. 1998, 55(9): 1369-1375.
[16] Kubinyi H. QSAR and 3D QSAR in drug design Part 1: methodology. Drug Discovery Today. 1997, 2(11): 457-467.
[17] Hopfinger A.J. A QSAR investigation of dihydrofolate reductase inhibition by Baker triazines based upon molecular shape analysis. Journal of the American Chemical Society. 1980, 102(24): 7196-7206.
[18] Crippen G.M. Quantitative structure-activity relationships by distance geometry: thyroxine binding site. Journal of Medicinal Chemistry. 1981, 24(2): 198-203.
[19] Klebe G.,Abraham U.,Mietzner T. Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. Journal of Medicinal Chemistry. 1994, 37(24): 4130-4146.
[20] Ruan Z.,Wang H.,Ren Y., et al. Pseudo receptor probes: A novel pseudo receptor-based QSAR method and application into studies on a new kind of selective vascular endothelial growth factor-2 receptor inhibitors. Chemometrics and Intelligent Laboratory Systems. 2008, 92(2): 157-168.
[21] Cramer III R.D.,Patterson D.E.,Bunce J.D. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. Journal of the American Chemical Society. 1988, 110(18): 5959-5967.
[22]侯廷军,徐筱杰.比较分子场分析方法研究的最新进展化学进展. 2001, 13(6): 436-440.
[23] De Groot M.J. Designing better drugs: predicting cytochrome P450 metabolism. Drug Discovery Today. 2006, 11(13-14): 601-606.
[24] Lozano J.J.,Pastor M.,Cruciani G., et al. 3D-QSAR methods on the basis of ligand–receptor complexes. Application of COMBINE and GRID/GOLPE methodologies to a series of CYP1A2 ligands. Journal of Computer-Aided Molecular Design. 2000, 14(4): 341-353.
[25] Poso A.,Gynther J.,Juvonen R. A comparative molecular field analysis of cytochrome P450 2A5 and 2A6 inhibitors. Journal of Computer-Aided Molecular Design. 2001, 15(3): 195-202.
[26] Ekins S.,Bravi G.,Ring B.J., et al. Three-dimensional quantitative structure activity relationship analyses of substrates for CYP2B6. Journal of Pharmacology and ExperimentalTherapeutics. 1999, 288(1): 21-29.
[27] Jones J.P.,He M.,Trager W.F., et al. Three-dimensional quantitative structure-activity relationship for inhibitors of cytochrome P4502C9. Drug Metabolism and Disposition. 1996, 24(1): 1-6.
[28] Afzelius L.,Zamora I.,Masimirembwa C.M., et al. Conformer-and alignment-independent model for predicting structurally diverse competitive CYP2C9 inhibitors. Journal of Medicinal Chemistry. 2004, 47(4): 907-914.
[29] Locuson C.W.,Rock D.A.,Jones J.P. Quantitative Binding Models for CYP2C9 Based on Benzbromarone Analogues. Biochemistry. 2004, 43(6948-6958.
[30] Schneider G.,Coassolo P.,LavéT. Combining in vitro and in vivo pharmacokinetic data for prediction of hepatic drug clearance in humans by artificial neural networks and multivariate statistical techniques. Journal of Medicinal Chemistry. 1999, 42(25): 5072-5076.
[31] Lee S.,Kim D. Equation chapter 1 section 1A new method for predicting human hepatic clearance from in vitro experimental data using molecular descriptors. Archives of Pharmacal Research. 2007, 30(2): 182-190.
[32] Lee P.H.,Cucurull-Sanchez L.,Lu J., et al. Development of in silico models for human liver microsomal stability. Journal of Computer-Aided Molecular Design. 2007, 21(12): 665-673.
[33] Chohan K.K.,Paine S.W.,Mistry J., et al. A rapid computational filter for cytochrome P450 1A2 inhibition potential of compound libraries. Journal of Medicinal Chemistry. 2005, 48(16): 5154-5161.
[34] Burton J.,Ijjaali I.,Barberan O., et al. Recursive partitioning for the prediction of cytochromes P450 2D6 and 1A2 inhibition: importance of the quality of the dataset. Journal of Medicinal Chemistry. 2006, 49(21): 6231-6240.
[35] Kriegl J.M.,Arnhold T.,Beck B., et al. Prediction of human cytochrome P450 inhibition using support vector machines. QSAR & Combinatorial Science. 2005, 24(4): 491-502.
[36] Li H.,Sun J.,Fan X., et al. Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction. Journal of Computer-Aided Molecular Design. 2008, 22(11): 843-855.
[37] Elbekai R.H.,El-Kadi A.O.S. Cytochrome P450 enzymes: central players in cardiovascular health and disease. Pharmacology & Therapeutics. 2006, 112(2): 564-587.
[38] Rushmore T.H.,Tony K.A. Pharmacogenomics, regulation and signaling pathways of phase I and II drug metabolizing enzymes. Current Drug Metabolism. 2002, 3(5): 481-490.
[39] Coon M.J.,Strobel H.W.,Boyer R.F. On the mechanism of hydroxylation reactions catalyzed by cytochrome P-450. Drug Metabolism and Disposition. 1973, 1(1): 92-97.
[40] Shaik S.,Kumar D.,de Visser S.P., et al. Theoretical perspective on the structure and mechanism of cytochrome P450 enzymes. Chemical Reviews. 2005, 105(6): 2279-2328.
[41] Lewis D.F.V.,Pratt J.M. The P 450 catalytic cycle and oxygenation mechanism. Drug Metabolism Reviews. 1998, 30(4): 739-786.
[42] Meunier B.,De Visser S.P.,Shaik S. Mechanism of oxidation reactions catalyzed by cytochrome P450 enzymes. Chemical Reviews. 2004, 104(9): 3947-3980.
[43] Werck-Reichhart D.,Feyereisen R. Cytochromes P450: a success story. Genome Biol. 2000, 1(6): 1-9.
[44] Denisov I.G.,Makris T.M.,Sligar S.G., et al. Structure and chemistry of cytochrome P450. Chemical Reviews. 2005, 105(6): 2253-2278.
[45] Hays A.M.A.,Dunn A.R.,Chiu R., et al. Conformational states of cytochrome P450cam revealed by trapping of synthetic molecular wires. Journal of Molecular Biology. 2004, 344(2): 455-469.
[46] Cojocaru V.,Winn P.J.,Wade R.C. The ins and outs of cytochrome P450s. Biochimica et Biophysica Acta (BBA)-General Subjects. 2007, 1770(3): 390-401.
[47] Rydberg P.,Rod T.H.,Olsen L., et al. Dynamics of water molecules in the active-site cavity of human cytochromes P450. The Journal of Physical Chemistry B. 2007, 111(19): 5445-5457.
[48] Williams P.A.,Cosme J.,Ward A., et al. Crystal structure of human cytochrome P450 2C9 with bound warfarin. Nature. 2003, 424(6947): 464-468.
[49] Wester M.R.,Yano J.K.,Schoch G.A., et al. The structure of human cytochrome P450 2C9 complexed with flurbiprofen at 2.0-resolution. Journal of Biological Chemistry. 2004, 279(34): 35630-35637.
[50] Rowland P.,Blaney F.E.,Smyth M.G., et al. Crystal structure of human cytochrome P450 2D6. Journal of Biological Chemistry. 2006, 281(11): 7614-7622.
[51] Ito Y.,Kondo H.,Goldfarb P.S., et al. Analysis of CYP2D6 substrate interactions by computational methods. Journal of Molecular Graphics and Modelling. 2008, 26(6): 947-956.
[52] Sun H.,Scott D.O. Structure‐ based Drug Metabolism Predictions for Drug Design. Chemical Biology & Drug Design. 2010, 75(1): 3-17.
[53] de Groot M.J.,Ackland M.J.,Horne V.A., et al. Novel approach to predicting P450-mediated drug metabolism: development of a combined protein and pharmacophore model for CYP2D6.Journal of Medicinal Chemistry. 1999, 42(9): 1515-1524.
[54] de Groot M.J.,Ekins S. Pharmacophore modeling of cytochromes P450. Advanced Drug Delivery Reviews. 2002, 54(3): 367-383.
[55] Freitas R.,Bauab R.,Montanari C. Novel Application of 2D and 3D-Similarity Searches To Identify Substrates among Cytochrome P450 2C9, 2D6, and 3A4. Journal of Chemical Information and Modeling. 2010, 50(1): 97-109.
[56] Gunes A.,Dahl M.L. Variation in CYP1A2 activity and its clinical implications: influence of environmental factors and genetic polymorphisms. Pharmacogenomics. 2008, 9(5): 625-637.
[57] Wang B.,Zhou S.F. Synthetic and natural compounds that interact with human cytochrome P450 1A2 and implications in drug development. Current Medicinal Chemistry. 2009, 16(31): 4066-4218.
[58] Sansen S.,Yano J.K.,Reynald R.L., et al. Adaptations for the oxidation of polycyclic aromatic hydrocarbons exhibited by the structure of human P450 1A2. Journal of Biological Chemistry. 2007, 282(19): 14348-14355.
[59] Lewis D.F.V.,Ito Y. Human CYPs involved in drug metabolism: structures, substrates and binding affinities. Expert Opinion on Drug Metabolism & Toxicology. 2010, 6(6): 661-674.
[60] Rendic S. Summary of information on human CYP enzymes: human P450 metabolism data. Drug Metabolism Reviews. 2002, 34(1-2): 83-448.
[61] Halgren T.A. Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry. 1996, 17(5-6): 490-519.
[62] Case D.,Darden T.,Cheatham III T., et al. AMBER 8. University of California, San Francisco. 2004,
[63] Huey R.,Morris G.M.,Olson A.J., et al. A semiempirical free energy force field with charge‐ based desolvation. Journal of Computational Chemistry. 2007, 28(6): 1145-1152.
[64] Schames J.,Henchman R.,Siegel J., et al. Discovery of a novel binding trench in HIV integrase. J. Med. Chem. 2004, 47(8): 1879-1881.
[65] Lin J.,Perryman A.,Schames J., et al. Computational drug design accommodating receptor flexibility: the relaxed complex scheme. J. Am. Chem. Soc. 2002, 124(20): 5632-5633.
[66] Efron B. Bootstrap methods: another look at the jackknife. The Annals of Statistics. 1979, 7(1): 1-26.
[67] Lewis D.,Ito Y. Human P450s involved in drug metabolism and the use of structural modelling for understanding substrate selectivity and binding affinity. Xenobiotica. 2009,39(8): 625-635.
[68] Kumar G.N.,Surapaneni S. Role of drug metabolism in drug discovery and development. Medicinal Research Reviews. 2001, 21(5): 397-411.
[69] Parikh A. , Josephy P.D. , Guengerich F.P. Selection and Characterization of Human Cytochrome P450 1A2 Mutants with Altered Catalytic Properties. Biochemistry. 1999, 38(17): 5283-5289.
[70] Hutchison C.A.,Phillips S.,Edgell M., et al. Mutagenesis at a specific position in a DNA sequence. Journal of Biological Chemistry. 1978, 253(18): 6551-6560.
[71] Liu J.,Ericksen S.S.,Sivaneri M., et al. The effect of reciprocal active site mutations in human cytochromes P450 1A1 and 1A2 on alkoxyresorufin metabolism. Archives of Biochemistry and Biophysics. 2004, 424(1): 33-43.
[2]许化夏,李培军,刘宛,宋玉芳.生物细胞色素P450的研究进展.农业环境保护. 2002, 2(12): 188-191.
[3] Estabrook R.W. A passion for P450s (remembrances of the early history of research on cytochrome P450). Drug Metabolism and Disposition. 2003, 31(12): 1461-1473.
[4] Miller J.A. The metabolism of xenobiotics to reactive electrophiles in chemical carcinogenesis and mutagenesis: a collaboration with Elizabeth Cavert Miller and our associates. Drug metabolism reviews. 1998, 30(4): 645-674.
[5] Mueller G.C.,Miller J. The reductive cleavage of 4-dimethylaminoazobenzene by rat liver: the intracellular distribution of the enzyme system and its requirement for triphosphopyridine nucleotide. Journal of Biological Chemistry. 1949, 180(3): 1125-1136.
[6] Mueller G.C.,Miller J. The Metabolism of Methylated Aminoazo Dyes. Journal of Biological Chemistry. 1953, 202(2): 579-587.
[7] Axelrod J. The enzymatic demethylation of ephedrine. Journal of Pharmacology and Experimental Therapeutics. 1955, 114(4): 430-438.
[8] Gillette J.R. Laboratory of Chemical Pharmacology, National Heart, Lung, and Blood Institute, NIH: A Short History. Annual Review of Pharmacology and Toxicology. 2000, 40(1): 19-41.
[9] Ryan K.J.,Engel L.L. Hydroxylation of steroids at carbon 21. Journal of Biological Chemistry. 1957, 225(1): 103-114.
[10] Mason H.,Fowlks W.,Peterson E. Oxygen transfer and electron transport by the phenolase complex1 Journal of the American Chemical Society. 1955, 77(10): 2914-2915.
[11] Hayaishi O.,Katagiri M.,Rothberg S. Mechanism of the pyrocatechase reaction. Journal of the American Chemical Society. 1955, 77(20): 5450-5451.
[12] Chance B. Techniques for the assay of the respiratory enzymes. Methods Enzymol. 1957, 4273-329.
[13] Chance B. Rapid and Sensitive Spectrophotometry. I. The Accelerated and Stopped‐ Flow Methods for the Measurement of the Reaction Kinetics and Spectra of Unstable Compounds inthe Visible Region of the Spectrum. Review of Scientific Instruments. 1951, 22(8): 619-627.
[14] Estabrook R.W. Mitochondrial respiratory control and the polarographic measurement of ADP: O ratios. Methods in enzymology. 1967, 1041-47.
[15] Klingenberg M. Pigments of rat liver microsomes. Archives of biochemistry and biophysics. 1958, 75(2): 376-386.
[16] Cooper D.,Estabrook R.,Rosenthal O. On the cytochromes in microsomes from cortex and medulla of steer adrenals. 1963, 22587.
[17] Omura T.,Sato R. A new cytochrome in liver microsomes. Journal of Biological Chemistry. 1962, 237(4): 1375-1376.
[18] Remmer H.,Merker H. Effect of drugs on the formation of smooth endoplasmic reticulum and drug-metabolizing enzymes. Annals of the New York Academy of Sciences. 1965, 123(Evaluation and Mechanisms of Drug Toxicity): 79-97.
[19] Cooper D.Y.,Levin S.,Narasimhulu S., et al. Photochemical action spectrum of the terminal oxidase of mixed function oxidase systems. Science. 1965, 147(3656): 400-402.
[20] Lu A.,Coon M. Role of hemoprotein P-450 in fatty acid omega-hydroxylation in a soluble enzyme system from liver microsomes. J Biol Chem. 1968, 32(243): 1331-1332.
[21] Porter T.D. Jud Coon: 35 years of P450 research, a synopsis of P450 history. Drug Metabolism and Disposition. 2004, 32(1): 1-6.
[22] Haugen D.,Van der Hoeven T.,Coon M. Purified liver microsomal cytochrome P-450. Separation and characterization of multiple forms. Journal of Biological Chemistry. 1975, 250(9): 3567-3570.
[23] Haugen D.,Coon M.J. Properties of electrophoretically homogeneous phenobarbital-inducible and beta-naphthoflavone-inducible forms of liver microsomal cytochrome P-450. Journal of Biological Chemistry. 1976, 251(24): 7929-7939.
[24] Lewis D.F.V. 57 varieties: the human cytochromes P450. pgs. 2004, 5(3): 305-318.
[25] Iyanagi T.,Mason H. Properties of hepatic reduced nicotinamide adenine dinucleotide phosphate-cytochrome c reductase. Biochemistry. 1973, 12(12): 2297-2308.
[26] Coon M.J.,Strobel H.W.,Boyer R.F. On the mechanism of hydroxylation reactions catalyzed by cytochrome P-450. Drug Metabolism and Disposition. 1973, 1(1): 92-97.
[27] Vermilion J.L.,Coon M.J. Purified liver microsomal NADPH-cytochrome P-450 reductase. Spectral characterization of oxidation-reduction states. Journal of Biological Chemistry. 1978, 253(8): 2694-2704.
[28] Vermilion J.,Ballou D.,Massey V., et al. Separate roles for FMN and FAD in catalysis by liver microsomal NADPH-cytochrome P-450 reductase. Journal of Biological Chemistry. 1981, 256(1): 266-277.
[29] White R.,Coon M. Oxygen activation by cytochrome P-450. Annual review of biochemistry. 1980, 49315-356.
[30] Khani S.C.,Zaphiropoulos P.G.,Fujita V.S., et al. cDNA and derived amino acid sequence of ethanol-inducible rabbit liver cytochrome P-450 isozyme 3a (P-450ALC). Proceedings of the National Academy of Sciences of the United States of America. 1987, 84(3): 638-642.
[31] Khani S.,Porter T.,Fujita V., et al. Organization and differential expression of two highly similar genes in the rabbit alcohol-inducible cytochrome P-450 subfamily. Journal of Biological Chemistry. 1988, 263(15): 7170-7175.
[32] Porter T.D.,Khani S.,Coon M.J. Induction and tissue-specific expression of rabbit cytochrome P450IIE1 and IIE2 genes. Molecular pharmacology. 1989, 36(1): 61-65.
[33] Nebert D.W.,Adesnik M.,Coon M.J., et al. The P450 gene superfamily: recommended nomenclature. Dna. 1987, 6(1): 1-11.
[34] Cosme J.,Johnson E.F. Engineering microsomal cytochrome P450 2C5 to be a soluble, monomeric enzyme. Journal of Biological Chemistry. 2000, 275(4): 2545-2553.
[35] Williams P.A.,Cosme J.,Sridhar V., et al. Mammalian Microsomal Cytochrome P450 Monooxygenase:: Structural Adaptations for Membrane Binding and Functional Diversity. Molecular Cell. 2000, 5(1): 121-131.
[36] Nelson D.R. The cytochrome P450 homepage. Human Genomics. 2009, 4(1): 59-65.
[37] Nelson D.,Koymans L.,Kamataki T., et al. IC Gunsalus & DW Nebert: P450 superfamily: update on new sequences, gene mapping, accession numbers and nomenclature. Pharmacogenetics. 1996, 61-42.
[38] Nelson D.R.,Kamataki T.,waxman D.J., et al. The P450 superfamily: update on new sequences, gene mapping, accession numbers, early trivial names of enzymes, and nomenclature. DNA and Cell Biology. 1993, 12(1): 1-51.
[39] De Montellano P.R.O. Cytochrome P450: structure, mechanism, and biochemistry. Plenum Pub Corp. 2005: 585-617.
[40] Nelson D.R.,Schuler M.A.,Paquette S.M., et al. Comparative genomics of rice and Arabidopsis. Analysis of 727 cytochrome P450 genes and pseudogenes from a monocot and a dicot. Plant Physiology. 2004, 135(2): 756-772.
[41] Tijet N.,Helvig C.,Feyereisen R. The cytochrome P450 gene superfamily in Drosophila melanogaster: annotation, intron-exon organization and phylogeny. Gene. 2001, 262(1-2): 189-198.
[42] Claudianos C.,Ranson H.,Johnson R., et al. A deficit of detoxification enzymes: pesticide sensitivity and environmental response in the honeybee. Insect Molecular Biology. 2006, 15(5): 615-636.
[43] Paquette S.M.,Bak S.,Feyereisen R. Intron-exon organization and phylogeny in a large superfamily, the paralogous cytochrome P450 genes of Arabidopsis thaliana. DNA and Cell Biology. 2000, 19(5): 307-317.
[44] Schuler M.A.,Werck-Reichhart D. Functional genomics of P450s. Annual Review of Plant Biology. 2003, 54(1): 629-667.
[45] Nelson D.R.,Zeldin D.C.,Hoffman S.M.G., et al. Comparison of cytochrome P450 (CYP) genes from the mouse and human genomes, including nomenclature recommendations for genes, pseudogenes and alternative-splice variants. Pharmacogenetics and Genomics. 2004, 14(1): 1-18.
[46] Debeljak N. , Fink M. , Rozman D. Many facets of mammalian lanosterol 14 [alpha]-demethylase from the evolutionarily conserved cytochrome P450 family CYP51. Archives of biochemistry and biophysics. 2003, 409(1): 159-171.
[47] Waterman M.R.,Lepesheva G.I. Sterol 14 [alpha]-demethylase, an abundant and essential mixed-function oxidase. Biochemical and biophysical research communications. 2005, 338(1): 418-422.
[48] Poulos T.L.,Finzel B.C.,Howard A.J. High-resolution crystal structure of cytochrome P450cam. Journal of molecular biology. 1987, 195(3): 687-700.
[49] Pochapsky T.C.,Kazanis S.,Dang M. Conformational Plasticity and Structure/Function Relationships in Cytochromes P450. Antioxidants & Redox Signaling. 2010, 13(8): 1273-1296.
[50]王斌,李德远.细胞色素P450的结构与催化机理.有机化学. 2009, 29(004): 658-662.
[51] Sigel A.,Sigel H.,Sigel R.K.O. The ubiquitous roles of cytochrome P450 proteins. West Sussex: Wiley. 2007: 27-53.
[52] Negishi M.,Iwasaki M.,Juvonen R.O., et al. Structural flexibility and functional versatility of cytochrome P450 and rapid evolution. Mutation Research/Fundamental and MolecularMechanisms of Mutagenesis. 1996, 350(1): 43-50.
[53] Baudry J.,Rupasinghe S.,Schuler M.A. Class-dependent sequence alignment strategy improves the structural and functional modeling of P450s. Protein Engineering Design and Selection. 2006, 19(8): 345-353.
[54] Lindberg R.L.P.,Negishi M. Alteration of mouse cytochrome P450coh substrate specificity by mutation of a single amino-acid residue. Nature. 1989, (339): 632-634.
[55] Schalk M.,Croteau R. A single amino acid substitution (F363I) converts the regiochemistry of the spearmint (-)-limonene hydroxylase from a C6-to a C3-hydroxylase. Proceedings of the National Academy of Sciences of the United States of America. 2000, 97(22): 11948-11953.
[56] Domanski T.,Halpert J. Analysis of mammalian cytochrome P450 structure and function by site-directed mutagenesis. Current Drug Metabolism. 2001, 2(2): 117-137.
[57] Rupasinghe S.,Schuler M.A. Homology modeling of plant cytochrome P450s. Phytochemistry Reviews. 2006, 5(2): 473-505.
[58] Gilbert L.I. Halloween genes encode P450 enzymes that mediate steroid hormone biosynthesis in Drosophila melanogaster. Molecular and cellular endocrinology. 2004, 215(1-2): 1-10.
[59] Scott J.G.,Wen Z. Cytochromes P450 of insects: the tip of the iceberg. Pest management science. 2001, 57(10): 958-967.
[60] Schuler M.A.,Duan H.,Bilgin M., et al. Arabidopsis cytochrome P450s through the looking glass: a window on plant biochemistry. Phytochemistry Reviews. 2006, 5(2): 205-237.
[61] Fujioka S. , Sakurai A. Biosynthesis and metabolism of brassinosteroids. Physiologia Plantarum. 1997, 100(3): 710-715.
[62] Szekeres M.,Németh K.,Koncz-Kálmán Z., et al. Brassinosteroids rescue the deficiency of CYP90, a cytochrome P450, controlling cell elongation and de-etiolation in Arabidopsis. Cell. 1996, 85(2): 171-182.
[63] Choe S.,Dilkes B.P.,Fujioka S., et al. The DWF4 gene of Arabidopsis encodes a cytochrome P450 that mediates multiple 22 a-hydroxylation steps in brassinosteroid biosynthesis. The Plant Cell Online. 1998, 10(2): 231-243.
[64] Kim T.W.,Hwang J.Y.,Kim Y.S., et al. Arabidopsis CYP85A2, a cytochrome P450, mediates the Baeyer-Villiger oxidation of castasterone to brassinolide in brassinosteroid biosynthesis. The Plant Cell Online. 2005, 17(8): 2397-2412.
[65] Nomura T.,Kushiro T.,Yokota T., et al. The last reaction producing brassinolide is catalyzed by cytochrome P-450s, CYP85A3 in tomato and CYP85A2 in Arabidopsis. Journal ofBiological Chemistry. 2005, 280(18): 17873-17879.
[66] Niwa R.,Matsuda T.,Yoshiyama T., et al. CYP306A1, a cytochrome P450 enzyme, is essential for ecdysteroid biosynthesis in the prothoracic glands of Bombyx and Drosophila. Journal of Biological Chemistry. 2004, 279(34): 35942-35949.
[67] Warren J.T.,Petryk A.,Marqués G., et al. Phantom encodes the 25-hydroxylase of Drosophila melanogaster and Bombyx mori: a P450 enzyme critical in ecdysone biosynthesis. Insect biochemistry and molecular biology. 2004, 34(9): 991-1010.
[68] Namiki T.,Niwa R.,Sakudoh T., et al. Cytochrome P450 CYP307A1/Spook: a regulator for ecdysone synthesis in insects. Biochemical and biophysical research communications. 2005, 337(1): 367-374.
[69] Choi M.H. , Skipper P.L. , Wishnok J.S., et al. Characterization of testosterone 11β-hydroxylation catalyzed by human liver microsomal cytochromes P450. Drug Metabolism and Disposition. 2005, 33(6): 714-718.
[70] Turk E.M.,Fujioka S.,Seto H., et al. CYP72B1 inactivates brassinosteroid hormones: an intersection between photomorphogenesis and plant steroid signal transduction. Plant Physiology. 2003, 133(4): 1643-1653.
[71] Nakamura M.,Satoh T.,Tanaka S.I., et al. Activation of the cytochrome P450 gene, CYP72C1, reduces the levels of active brassinosteroids in vivo. Journal of experimental botany. 2005, 56(413): 833-840.
[72] Williams D.R.,Fisher M.J.,Rees H.H. Characterization of ecdysteroid 26-hydroxylase: an enzyme involved in molting hormone inactivation. Archives of biochemistry and biophysics. 2000, 376(2): 389-398.
[73] Wen Z.,Pan L.,Berenbaum M.R., et al. Metabolism of linear and angular furanocoumarins by Papilio polyxenes CYP6B1 co-expressed with NADPH cytochrome P450 reductase. Insect biochemistry and molecular biology. 2003, 33(9): 937-947.
[74] Li X.,Baudry J.,Berenbaum M.R., et al. Structural and functional divergence of insect CYP6B proteins: From specialist to generalist cytochrome P450. Proceedings of the National Academy of Sciences of the United States of America. 2004, 101(9): 2939-2944.
[75] Yano J.K.,Hsu M.H.,Griffin K.J., et al. Structures of human microsomal cytochrome P450 2A6 complexed with coumarin and methoxsalen. Nature Structural & Molecular Biology. 2005, 12(9): 822-823.
[76] Gustafsson M.C.U. , Roitel O. , Marshall K.R., et al. Expression, Purification, andCharacterization of Bacillus subtilis Cytochromes P450 CYP102A2 and CYP102A3: Flavocytochrome Homologues of P450 BM3 from Bacillus megaterium. Biochemistry. 2004, 43(18): 5474-5487.
[77] Scheller U.,Zimmer T.,K rgel E., et al. Characterization of then-Alkane and Fatty Acid Hydroxylating Cytochrome P450 Forms 52A3 and 52A4. Archives of biochemistry and biophysics. 1996, 328(2): 245-254.
[78] Salaün J.,Helvig C. Cytochrome P450-dependent oxidation of fatty acids. Drug metabolism and drug interactions. 1995, 12(3-4): 261-283.
[79] Duan H.,Schuler M.A. Differential expression and evolution of the Arabidopsis CYP86A subfamily. Plant Physiology. 2005, 137(3): 1067-1081.
[80] Xiao F.,Goodwin S.M.,Xiao Y., et al. Arabidopsis CYP86A2 represses Pseudomonas syringae type III genes and is required for cuticle development. The EMBO Journal. 2004, 23(14): 2903-2913.
[81] Kandel S. , Morant M. , Benveniste I., et al. Cloning, functional expression, and characterization of CYP709C1, the first sub-terminal hydroxylase of long chain fatty acid in plants. Journal of Biological Chemistry. 2005, 280(43): 35881-35889.
[82] Oktia R.,Okita J. Cytochrome P450 4A fatty acid omega hydroxylases. Current Drug Metabolism. 2001, 2(3): 265-281.
[83] Henne K.R.,Kunze K.L.,Zheng Y.M., et al. Covalent Linkage of Prosthetic Heme to CYP4 Family P450 Enzymes. Biochemistry. 2001, 40(43): 12925-12931.
[84] Tomaszewski P. , Kubiak-Tomaszewska G. , Pachecka J. Cytochrome P450 polymorphism--molecular, metabolic, and pharmacogenetic aspects. II. Participation of CYP isoenzymes in the metabolism of endogenous substances and drugs. Acta Poloniae Pharmaceutica. 2008, 65(3): 307-318.
[85] Guengerich F. Cytochrome P450 enzymes in the generation of commercial products. Nature Reviews Drug Discovery. 2002, 1(5): 359-366.
[86] Weide J.v.d.,Steijns L.S.W. Cytochrome P450 enzyme system: genetic polymorphisms and impact on clinical pharmacology. Annals of clinical biochemistry. 1999, 36722-729.
[87] Issa A. Personalized Medicine and the Practice of Medicine in the 21st Century. McGill Journal of Medicine. 2007, 10(1): 53-57.
[88] Ingelman-Sundberg M. The human genome project and novel aspects of cytochrome P450 research. Toxicology and Applied Pharmacology. 2005, 207(2): 52-56.
[89] Nelson D.,Zeldin D.,Hoffman S., et al. Comparison of cytochrome P450 (CYP) genes from the mouse and human genomes, including nomenclature recommendations for genes, pseudogenes and alternative-splice variants. Pharmacogenetics. 2004, 14(1): 1-18.
[90] Yao A.,Charlab R.,Li P. Systematic identification of pseudogenes through whole genome expression evidence profiling. Nucleic Acids Research. 2006, 34(16): 4477-4485.
[91] Shimizu T.,Ochiai H.,?sell F., et al. Bioinformatics research on inter-racial difference in drug metabolism II. Analysis on relationship between enzyme activities of CYP2D6 and CYP2C19 and their relevant genotypes. Drug Metabolism and Pharmacokinetics. 2003, 18(1): 71-78.
[92] Shimizu T.,Ochiai H.,?sell F., et al. Bioinformatics research on inter-racial difference in drug metabolism I. Analysis on frequencies of mutant alleles and poor metabolizers on CYP2D6 and CYP2C19. Drug Metabolism and Pharmacokinetics. 2003, 18(1): 48-70.
[93] Zhou S.,Liu J.,Chowbay B. Polymorphism of human cytochrome P450 enzymes and its clinical impact. Drug metabolism reviews. 2009, 41(2): 89-295.
[94] Yue P.,Melamud E.,Moult J. SNPs 3 D: Candidate gene and SNP selection for association studies. BMC bioinformatics. 2006, 7(1): 166-180.
[95] Ferrer-Costa C.,Gelpi J.,Zamakola L., et al. PMUT: a web-based tool for the annotation of pathological mutations on proteins. Bioinformatics Applications Note. 2005, 21(14): 3176-3178.
[96] Stitziel N.,Binkowski T.,Tseng Y., et al. topoSNP: a topographic database of non-synonymous single nucleotide polymorphisms with and without known disease association. Nucleic Acids Research. 2004, 32(Database Issue): 520-522.
[97] Wang L.,Li Y.,Zhou S. A bioinformatics approach for the phenotype prediction of non-synonymous single nucleotide polymorphisms in human cytochrome P450s. Drug Metabolism and Disposition. 2009, 37(5): 977-991.
[98] Hodel E.,Ley S.,Qi W., et al. A microarray-based system for the simultaneous analysis of single nucleotide polymorphisms in human genes involved in the metabolism of anti-malarial drugs. Malaria Journal. 2009, 8(1): 285-294.
[99] Wen S.,Wang H.,Sun O., et al. Rapid detection of the known SNPs of CYP2C9 using oligonucleotide microarray. World Journal of Gastroenterology. 2003, 9(6): 1342-1346.
[100] Wen S.,Wang H.,Ding Y., et al. Screening of 12 SNPs of CYP3A4 in a Chinese population using oligonucleotide microarray. Genetic Testing. 2004, 8(4): 411-416.
[101] Rieder M.,Livingston R.,Stanaway I., et al. The environmental genome project: referencepolymorphisms for drug metabolism genes and genome-wide association studies. Drug metabolism reviews. 2008, 40(2): 241-261.
[102] de Leon J.,Susce M.,Johnson M., et al. DNA Microarray Technology in the Clinical Environment: The AmpliChip CYP450 Test for CYP2D6 and CYP2C19 Genotyping. CNS spectrums. 2009, 14(1): 19-34.
[103] Langenfeld E.,Meyer H.,Marcus K. Quantitative analysis of highly homologous proteins: the challenge of assaying the“CYP-ome”by mass spectrometry. Analytical and Bioanalytical Chemistry. 2008, 392(6): 1123-1134.
[104] Chen C. , Ma X. , Malfatti M., et al. A comprehensive investigation of 2-amino-1-methyl-6-phenylimidazo [4, 5-b] pyridine (PhIP) metabolism in the mouse using a multivariate data analysis approach. Chemical research in toxicology. 2007, 20(3): 531-542.
[105] Chen C.,Meng L.,Ma X., et al. Urinary metabolite profiling reveals CYP1A2-mediated metabolism of NSC686288 (aminoflavone). Journal of Pharmacology and Experimental Therapeutics. 2006, 318(3): 1330-1342.
[106] Crooke P.S.,Ritchie M.D.,Hachey D.L., et al. Estrogens, Enzyme Variants, and Breast Cancer: A Risk Model. Cancer Epidemiology Biomarkers & Prevention. 2006, 15(9): 1620-1629.
[107] Tang Z.,Martin M.,Guengerich F. Elucidation of Functions of Human Cytochrome P450 Enzymes: Identification of Endogenous Substrates in Tissue Extracts Using Metabolomic and Isotopic Labeling Approaches. Analytical Chemistry. 2009, 81(8): 3071-3078.
[1] Danielson P. The cytochrome P450 superfamily: biochemistry, evolution and drug metabolism in humans. Current Drug Metabolism. 2002, 3(6): 561-597.
[2] Hakkola J.,Tanaka E.,Pelkonen O. Developmental expression of cytochrome P450 enzymes in human liver. Pharmacology & toxicology. 1998, 82(5): 209-217.
[3] Wienkers L.C.,Heath T.G. Predicting in vivo drug interactions from in vitro drug discovery data. Nature Reviews Drug Discovery. 2005, 4(10): 825-833.
[4]刘端.细胞色素P450基因单核苷酸多态性对药物安全性影响评价体系的建立和应用[博士论文].西安:西北大学. 2010:
[5] Ingelman-Sundberg M. Polymorphism of cytochrome P450 and xenobiotic toxicity. Toxicology. 2002, 181447-452.
[6] Crawford D.C.,Akey D.T.,Nickerson D.A. The patterns of natural variation in human genes. Annual Review of Genomics and Human Genetics. 2005, 6(1): 287-312.
[7] Halushka M.K.,Fan J.B.,Bentley K., et al. Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis. Nature Genetics. 1999, 22(3): 239-247.
[8] Cargill M.,Altshuler D.,Ireland J., et al. Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nature Genetics. 1999, 22(3): 231-238.
[9] Sim S.C.,Miller W.L.,Zhong X.B., et al. Nomenclature for alleles of the cytochrome P450 oxidoreductase gene. Pharmacogenetics and genomics. 2009, 19(7): 565-566.
[10] Sim S.C.,Ingelman-Sundberg M. The Human Cytochrome P450 (CYP) Allele Nomenclature website: A peer-reviewed database of CYP variants and their associated effects. Human Genomics. 2010, 4(4): 278-281.
[11] Ingelman-Sundberg M.,Daly A.K.,Oscarson M., et al. Human cytochrome P450 (CYP) genes: recommendations for the nomenclature of alleles. Pharmacogenetics and genomics. 2000, 10(1): 91-93.
[12] Dahl M.L.,Bertilsson L.,Nordin C. Steady-state plasma levels of nortriptyline and its 10-hydroxy metabolite: relationship to theCYP2D6 genotype. Psychopharmacology. 1996, 123(4): 315-319.
[13] Fjordside L.,Jeppesen U.,Eap C., et al. The stereoselective metabolism of fluoxetine in poor and extensive metabolizers of sparteine. Pharmacogenetics and genomics. 1999, 9(1): 55-60.
[14] Crewe H.K.,Ellis S.W.,Lennard M.S., et al. Variable contribution of cytochromes p450 2d6, 2c9 and 3a4 to the 4-hydroxylation of tamoxifen by human liver microsomes* 1. Biochemical pharmacology. 1997, 53(2): 171-178.
[15] Takahashi H. , Echizen H. Pharmacogenetics of warfarin elimination and its clinical implications. Clinical pharmacokinetics. 2001, 40(8): 587-603.
[16] Varenhorst C.,James S.,Erlinge D., et al. Genetic variation of CYP2C19 affects both pharmacokinetic and pharmacodynamic responses to clopidogrel but not prasugrel in aspirin-treated patients with coronary artery disease. European heart journal. 2009, 30(14): 1744-1752.
[17] Brandt J.,Close S.,Iturria S., et al. Common polymorphisms of CYP2C19 and CYP2C9 affect the pharmacokinetic and pharmacodynamic response to clopidogrel but not prasugrel. Journal of Thrombosis and Haemostasis. 2007, 5(12): 2429-2436.
[18] Dai D.,Zeldin D.C.,Blaisdell J.A., et al. Polymorphisms in human CYP2C8 decrease metabolism of the anticancer drug paclitaxel and arachidonic acid. Pharmacogenetics and genomics. 2001, 11(7): 597-607.
[19] Rendic S. Summary of information on human CYP enzymes: human P450 metabolism data. Drug metabolism reviews. 2002, 34(1): 83-448.
[20] Nelson D.R. Introductory remarks on human CYPs. Drug metabolism reviews. 2002, 34(1-2): 1-5.
[21] Antony T.R.T.,Nagarajan S. DrugMetZ DB: an anthology of human drug metabolizing Chytochrome P450 enzymes. Bioinformation. 2006, 1(7): 248-250.
[22] Preissner S.,Kroll K.,Dunkel M., et al. SuperCYP: a comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions. Nucleic Acids Research. 2010, 38(suppl 1): 237-243.
[23] Lisitsa A.,Guseva S.,Karuzina I., et al. Cytochrome P450 database. SAR and QSAR in Environmental Research. 2001, 12(4): 359-366.
[24] Fischer M.,Knoll M.,Sirim D., et al. The Cytochrome P450 Engineering Database: a navigation and prediction tool for the cytochrome P450 protein family. Bioinformatics. 2007, 23(15): 2015-2017.
[25] Van der Weide J.,Steijns L.S.W. Cytochrome P450 enzyme system: genetic polymorphisms and impact on clinical pharmacology. Annals of clinical biochemistry. 1999, 36722-729.
[26] Jain K.K. Applications of AmpliChip CYP450. Molecular Diagnosis. 2005, 9(3): 119-127.
[27] van Schaik R.H.N. CYP450 pharmacogenetics for personalizing cancer therapy. Drug Resistance Updates. 2008, 11(3): 77-98.
[28] Ahn C. Pharmacogenomics in drug discovery and development. Genomics & Informatics. 2007, 5(2): 41-45.
[29] Kusama M.,Maeda K.,Chiba K., et al. Prediction of the effects of genetic polymorphism on the pharmacokinetics of CYP2C9 substrates from in vitro data. Pharmaceutical research. 2009, 26(4): 822-835.
[30] Dickinson G.L.,Rezaee S.,Proctor N.J., et al. Incorporating in vitro information on drug metabolism into clinical trial simulations to assess the effect of CYP2D6 polymorphism on pharmacokinetics and pharmacodynamics: dextromethorphan as a model application. The Journal of Clinical Pharmacology. 2007, 47(2): 175-186.
[31] Sirim D.,Wagner F.,Lisitsa A., et al. The Cytochrome P 450 Engineering Database: integration of biochemical properties. BMC biochemistry. 2009, 10(1): 27-30.
[1]莫莉,黄大毛,唐发清.分子动态模拟及其在生物大分子研究中的应用.生命的化学. 2007, 27(003): 243-245.
[2]陈敏伯.计算化学:从理论化学到分子模拟.北京:科学出版社. 2009: 51-60.
[3] Karplus M.,McCammon J.A. Molecular dynamics simulations of biomolecules. Nature Structural & Molecular Biology. 2002, 9(9): 646-652.
[4] Alder B.,Wainwright T. Studies in molecular dynamics. I. General method. The Journal of Chemical Physics. 1959, 31(459-467.
[5] Rahman A. Correlations in the motion of atoms in liquid argon. Phys. Rev. 1964, 136(2A): 405-411.
[6] Rahman A.,Stillinger F.H. Molecular dynamics study of liquid water. The Journal of Chemical Physics. 1971, 55(7): 3336-3359.
[7] McCammon J.A.,Gelin B.R.,Karplus M. Dynamics of folded proteins. Nature. 1977, 267(5612): 585-590.
[8] Ichiye T.,Karplus M. Fluorescence depolarization of tryptophan residues in proteins: a molecular dynamics study. Biochemistry. 1983, 22(12): 2884-2893.
[9] Levy R.M.,Karplus M.,Wolynes P.G. NMR relaxation parameters in molecules with internal motion: exact Langevin trajectory results compared with simplified relaxation models. Journal of the American Chemical Society. 1981, 103(20): 5998-6011.
[10] Olejniczak E.,Dobson C.,Karplus M., et al. Motional averaging of proton nuclear Overhauser effects in proteins. Predictions from a molecular dynamics simulation of lysozyme. Journal of the American Chemical Society. 1984, 106(7): 1923-1930.
[11] Cusack S.,Smith J.,Finney J., et al. Low frequency dynamics of proteins studied by neutron time-of-flight spectroscopy. Physica B+ C. 1986, 136(1-3): 256-259.
[12] Brünger A.,Brooks C.L.,Karplus M. Active site dynamics of ribonuclease. Proceedings of the National Academy of Sciences of the United States of America. 1985, 82(24): 8458-8462.
[13] Nadler W.,Brünger A.T.,Schulten K., et al. Molecular and stochastic dynamics of proteins. Proceedings of the National Academy of Sciences of the United States of America. 1987, 84(22): 7933-7937.
[14] Brünger A.T.,Kuriyan J.,Karplus M. Crystallographic R factor refinement by molecular dynamics. Science. 1987, 235(4787): 458-460.
[15] Brooks B.,Karplus M. Normal modes for specific motions of macromolecules: application to the hinge-bending mode of lysozyme. Proceedings of the National Academy of Sciences of the United States of America. 1985, 82(15): 4995-4999.
[16] Colonna-Cesari F.,Perahia D.,Karplus M., et al. Interdomain motion in liver alcohol dehydrogenase. Structural and energetic analysis of the hinge bending mode. Journal of Biological Chemistry. 1986, 261(32): 15273-15279.
[17] Harvey S.C.,Prabhakaran M.,Mao B., et al. Phenylalanine transfer RNA: molecular dynamics simulation. Science. 1984, 223(4641): 1189-1191.
[18] Case D.,Karplus M. Dynamics of ligand binding to heme proteins* 1. Journal of Molecular Biology. 1979, 132(3): 343-368.
[19] Brooks B.,Karplus M. Harmonic dynamics of proteins: normal modes and fluctuations in bovine pancreatic trypsin inhibitor. Proceedings of the National Academy of Sciences of the United States of America. 1983, 80(21): 6571-6575.
[20] Irikura K.,Tidor B.,Brooks B., et al. Transition from B to Z DNA: contribution of internal fluctuations to the configurational entropy difference. Science. 1985, 229(4713): 571-572.
[21] Karplus M. Molecular dynamics of biological macromolecules: A brief history and perspective. Biopolymers. 2003, 68(3): 350-358.
[22] Nakajima N.,Nakamura H.,Kidera A. Multicanonical ensemble generated by molecular dynamics simulation for enhanced conformational sampling of peptides. The Journal of Physical Chemistry B. 1997, 101(5): 817-824.
[23] Daggett V.,Kollman P.A.,Kuntz I.D. A molecular dynamics simulation of polyalanine: An analysis of equilibrium motions and helix–coil transitions. Biopolymers. 1991, 31(9): 1115-1134.
[24] van Gunsteren W.F.,Dolenc J.,Mark A.E. Molecular simulation as an aid to experimentalists. Current opinion in structural biology. 2008, 18(2): 149-153.
[25] Lindorff-Larsen K.,Best R.B.,DePristo M.A., et al. Simultaneous determination of protein structure and dynamics. Nature. 2005, 433(7022): 128-132.
[26] Faure P.,Micu A.,Perahia D., et al. Correlated intramolecular motions and diffuse x–ray scattering in lysozyme. Nature Structural & Molecular Biology. 1994, 1(2): 124-128.
[27] Wang W.,Donini O.,Reyes C.M., et al. Biomolecular simulations: recent developments inforce fields, simulations of enzyme catalysis, protein-ligand, protein-protein, and protein-nucleic acid noncovalent interactions. Annual Review of Biophysics and Biomolecular Structure. 2001, 30(1): 211-243.
[28] Carlson H.A.,McCammon J.A. Accommodating protein flexibility in computational drug design. Molecular Pharmacology. 2000, 57(2): 213-218.
[29] Kuwata K.,Matumoto T.,Cheng H., et al. NMR-detected hydrogen exchange and molecular dynamics simulations provide structural insight into fibril formation of prion protein fragment 106–126. Proceedings of the National Academy of Sciences of the United States of America. 2003, 100(25): 14790-14795.
[30] Xu Y.,Shen J.,Luo X., et al. Conformational transition of amyloidβ-peptide. Proceedings of the National Academy of Sciences of the United States of America. 2005, 102(15): 5403-5407.
[31] Tajkhorshid E.,Nollert P.,Jensen M., et al. Control of the selectivity of the aquaporin water channel family by global orientational tuning. Science. 2002, 296(5567): 525-530.
[32] Baker D. A surprising simplicity to protein folding. Nature. 2000, 405(6782): 39-42.
[33] Duan Y. , Kollman P.A. Pathways to a protein folding intermediate observed in a 1-microsecond simulation in aqueous solution. Science. 1998, 282(5389): 740-744.
[34] Scheraga H.A.,Khalili M.,Liwo A. Protein-folding dynamics: overview of molecular simulation techniques. Annual Review of Physical Chemistry. 2007, 58(1): 57-83.
[35] Lu H.,Schulten K. Steered molecular dynamics simulations of force‐ induced protein domain unfolding. Proteins: Structure, Function, and Bioinformatics. 1999, 35(4): 453-463.
[36] Liu S.,Fan S.,Sun Z. Structural and functional characterization of the human CCR5 receptor in complex with HIV gp120 envelope glycoprotein and CD4 receptor by molecular modeling studies. Journal of Molecular Modeling. 2003, 9(5): 329-336.
[37] Wlodawer A. , Vondrasek J. Inhibitors of HIV-1 protease: A Major Success of Structure-Assisted Drug Design 1. Annual Review of Biophysics and Biomolecular Structure. 1998, 27(1): 249-284.
[38] Perryman A.L.,Lin J.H.,McCammon J.A. HIV‐ 1 protease molecular dynamics of a wild‐ type and of the V82F/I84V mutant: Possible contributions to drug resistance and a potential new target site for drugs. Protein Science. 2004, 13(4): 1108-1123.
[39] Cheatham T.E. Simulation and modeling of nucleic acid structure, dynamics and interactions. Current opinion in structural biology. 2004, 14(3): 360-367.
[40] Song C.,Xia Y.,Zhao M., et al. The effect of salt concentration on DNA conformationtransition: a molecular-dynamics study. Journal of Molecular Modeling. 2006, 12(3): 249-254.
[41] Chang Y.T.,Loew G.H. Molecular dynamics simulations of P450 BM3--examination of substrate-induced conformational change. Journal of biomolecular structure & dynamics. 1999, 16(6): 1189-1203.
[42] Wade R.C.,Gabdoulline R.R.,Lüdemann S.K., et al. Electrostatic steering and ionic tethering in enzyme–ligand binding: Insights from simulations. Proceedings of the National Academy of Sciences of the United States of America. 1998, 95(11): 5942-5949.
[43] Bathelt C.,Schmid R.D.,Pleiss J. Regioselectivity of CYP2B6: homology modeling, molecular dynamics simulation, docking. Journal of Molecular Modeling. 2002, 8(11): 327-335.
[44] Venhorst J.,Ter Laak A.M.,Commandeur J.N.M., et al. Homology modeling of rat and human cytochrome P450 2D (CYP2D) isoforms and computational rationalization of experimental ligand-binding specificities. Journal of medicinal chemistry. 2003, 46(1): 74-86.
[45] Paulsen M.D.,Ornstein R.L. Dramatic differences in the motions of the mouth of open and closed cytochrome P450BM‐ 3 by molecular dynamics simulations. Proteins: Structure, Function, and Bioinformatics. 1995, 21(3): 237-243.
[46] Lüdemann S.K.,Carugo O.,Wade R.C. Substrate access to cytochrome P450cam: a comparison of a thermal motion pathway analysis with molecular dynamics simulation data. Journal of Molecular Modeling. 1997, 3(8): 369-374.
[47] Winn P.J.,Lüdemann S.K.,Gauges R., et al. Comparison of the dynamics of substrate access channels in three cytochrome P450s reveals different opening mechanisms and a novel functional role for a buried arginine. Proceedings of the National Academy of Sciences of the United States of America. 2002, 99(8): 5361-5366.
[48] Helms V.,Wade R.C. Thermodynamics of water mediating protein-ligand interactions in cytochrome P450cam: a molecular dynamics study. Biophysical journal. 1995, 69(3): 810-824.
[49] Helms V.,Wade R.C. Hydration energy landscape of the active site cavity in cytochrome P450cam. Proteins: Structure, Function, and Bioinformatics. 1998, 32(3): 381-396.
[50] Arnold G.E.,Ornstein R.L. Molecular dynamics study of time-correlated protein domain motions and molecular flexibility: cytochrome P450BM-3. Biophysical journal. 1997, 73(3): 1147-1159.
[51] Paulsen M.D. , Ornstein R.L. Binding free energy calculations for P450cam-substrate complexes. Protein engineering. 1996, 9(7): 567-571.
[52] Szklarz G.D.,Paulsen M.D. Molecular modeling of cytochrome P450 1A1: enzyme-substrate interactions and substrate binding affinities. Journal of Biomolecular Structure & Dynamics. 2002, 20(2): 155-162.
[53] Helms V.,Wade R.C. Computational alchemy to calculate absolute protein-ligand binding free energy. Journal of the American Chemical Society. 1998, 120(12): 2710-2713.
[54] KeserüG.M.,Kolossváry I.,Bertók B. Cytochrome P-450 catalyzed insecticide metabolism. Prediction of regio-and stereoselectivity in the primer metabolism of carbofuran: A theoretical study. Journal of the American Chemical Society. 1997, 119(22): 5126-5131.
[55] Harris D.L.,Loew G.H. Investigation of the proton-assisted pathway to formation of the catalytically active, ferryl species of P450s by molecular dynamics studies of P450eryF. Journal of the American Chemical Society. 1996, 118(27): 6377-6387.
[56] Park J.Y.,Harris D. Construction and assessment of models of CYP2E1: Predictions of metabolism from docking, molecular dynamics, and density functional theoretical calculations. Journal of Medicinal Chemistry. 2003, 46(9): 1645-1660.
[57] Harris D.,Loew G. Prediction of regiospecific hydroxylation of camphor analogs by cytochrome P450cam. Journal of the American Chemical Society. 1995, 117(10): 2738-2746.
[58] Fahmy A.,Wagner G. TreeDock: A tool for protein docking based on minimizing van der Waals energies. Journal of the American Chemical Society. 2002, 124(7): 1241-1250.
[59]段爱霞,陈晶,刘宏德, et al.分子对接方法的应用与发展.分析科学学报. 2009, 25(4):473-477.
[60] Meiler J. , Baker D. ROSETTALIGAND: Protein–small molecule docking with full side‐ chain flexibility. Proteins: Structure, Function, and Bioinformatics. 2006, 65(3): 538-548.
[61] Taylor R.D.,Jewsbury P.J.,Essex J.W. A review of protein-small molecule docking methods. Journal of computer-aided molecular design. 2002, 16(3): 151-166.
[62] Stoddard B.L.,Koshland D.E. Prediction of the structure of a receptor–protein complex using a binary docking method. Nature. 1992, 358(27): 774-776.
[63] Berchanski A.,Shapira B.,Eisenstein M. Hydrophobic complementarity in protein–protein docking. Proteins: Structure, Function, and Bioinformatics. 2004, 56(1): 130-142.
[64] Duhovny D.,Nussinov R.,Wolfson H. Efficient unbound docking of rigid molecules. Algorithms in Bioinformatics. 2002, 2452(185-200.
[65] Sun Y.,Ewing T.,Skillman A., et al. CombiDOCK: structure-based combinatorial docking andlibrary design. Journal of computer-aided molecular design. 1998, 12(6): 597-604.
[66] Oshiro C.M.,Kuntz I.D.,Dixon J.S. Flexible ligand docking using a genetic algorithm. Journal of computer-aided molecular design. 1995, 9(2): 113-130.
[67] Mangoni M.,Roccatano D.,Di Nola A. Docking of flexible ligands to flexible receptors in solution by molecular dynamics simulation. Proteins: Structure, Function, and Bioinformatics. 1999, 35(2): 153-162.
[68] Lybrand T.P. Ligand--protein docking and rational drug design. Current opinion in structural biology. 1995, 5(2): 224-228.
[69] Jenkins J.L.,Bender A.,Davies J.W. In silico target fishing: Predicting biological targets from chemical structure. Drug Discovery Today: Technologies. 2007, 3(4): 413-421.
[70] Hermann J.C.,Marti-Arbona R.,Fedorov A.A., et al. Structure-based activity prediction for an enzyme of unknown function. Nature. 2007, 448(7155): 775-779.
[71] Leach A.R.,Shoichet B.K.,Peishoff C.E. Prediction of protein-ligand interactions. Docking and scoring: successes and gaps. Journal of medicinal chemistry. 2006, 49(20): 5851-5855.
[72] de Graaf C.,Vermeulen N.P.E.,Feenstra K.A. Cytochrome P450 in silico: an integrative modeling approach. Journal of Medicinal Chemistry. 2005, 48(8): 2725-2755.
[73] de Groot M.J.,Ekins S. Pharmacophore modeling of cytochromes P450. Advanced drug delivery reviews. 2002, 54(3): 367-383.
[74] Hritz J.,de Ruiter A.,Oostenbrink C. Impact of plasticity and flexibility on docking results for cytochrome P450 2D6: a combined approach of molecular dynamics and ligand docking. Journal of medicinal chemistry. 2008, 51(23): 7469-7477.
[75] Kramer B.,Rarey M.,Lengauer T. Evaluation of the FLEXX incremental construction algorithm for protein–ligand docking. Proteins: Structure, Function, and Bioinformatics. 1999, 37(2): 228-241.
[76] Bissantz C.,Folkers G.,Rognan D. Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. Journal of Medicinal Chemistry. 2000, 43(25): 4759-4767.
[77] Poornima C.,Dean P. Hydration in drug design. 1. Multiple hydrogen-bonding features of water molecules in mediating protein-ligand interactions. Journal of Computer-Aided Molecular Design. 1995, 9(6): 500-512.
[78] Wester M.R.,Johnson E.F.,Marques-Soares C., et al. Structure of a substrate complex of mammalian cytochrome P450 2C5 at 2.3 resolution: evidence for multiple substrate bindingmodes. Biochemistry. 2003, 42(21): 6370-6379.
[79] Williams P.A.,Cosme J.,Ward A., et al. Crystal structure of human cytochrome P450 2C9 with bound warfarin. Nature. 2003, 424(6947): 464-468.
[80] Wester M.R.,Yano J.K.,Schoch G.A., et al. The structure of human cytochrome P450 2C9 complexed with flurbiprofen at 2.0- resolution. Journal of Biological Chemistry. 2004, 279(34): 35630-35637.
[81] de Graaf C.,Pospisil P.,Pos W., et al. Binding mode prediction of cytochrome p450 and thymidine kinase protein-ligand complexes by consideration of water and rescoring in automated docking. Journal of medicinal chemistry. 2005, 48(7): 2308-2318.
[82] Keser G.M. A virtual high throughput screen for high affinity cytochrome P450cam substrates. Implications for in silico prediction of drug metabolism. Journal of Computer-Aided Molecular Design. 2001, 15(7): 649-657.
[83] De Voss J.J.,Sibbesen O.,Zhang Z., et al. Substrate docking algorithms and prediction of the substrate specificity of cytochrome P450cam and its L244A mutant. Journal of the American Chemical Society. 1997, 119(24): 5489-5498.
[84] Verras A.,Kuntz I.D.,de Montellano P.R.O. Computer-assisted design of selective imidazole inhibitors for cytochrome p450 enzymes. Journal of Medicinal Chemistry. 2004, 47(14): 3572-3579.
[85] García A.E. Large-amplitude nonlinear motions in proteins. Physical Review Letters. 1992, 68(17): 2696-2699.
[86] Amadei A.,Linssen A.B.M.,Berendsen H.J.C. Essential dynamics of proteins. Proteins: Structure Function and Genetics. 1993, 17(412-425.
[87] Grubmüller H. Predicting slow structural transitions in macromolecular systems: Conformational flooding. Physical Review E. 1995, 52(3): 2893-2906.
[88] Hayward S.,de Groot B.L. Normal modes and essential dynamics. Methods in Molecular Biology. 2008, 443(1): 89-106.
[89] Van Aalten D.,De Groot B.,Findlay J., et al. A comparison of techniques for calculating protein essential dynamics. Journal of computational chemistry. 1997, 18(2): 169-181.
[90] Van Aalten D.,Conn D.,De Groot B., et al. Protein dynamics derived from clusters of crystal structures. Biophysical journal. 1997, 73(6): 2891-2896.
[91] De Groot B.,Hayward S.,Van Aalten D., et al. Domain motions in bacteriophage T 4 lysozyme: A comparison between molecular dynamics and crystallographic data. ProteinsStructure Function and Genetics. 1998, 31(2): 116-127.
[92] Qian B.,Ortiz A.R.,Baker D. Improvement of comparative model accuracy by free-energy optimization along principal components of natural structural variation. Proceedings of the National Academy of Sciences of the United States of America. 2004, 101(43): 15346-15351.
[93] Nebert D.,Russell D. Clinical importance of the cytochromes P450. The Lancet. 2002, 360(9340): 1155-1162.
[94] Hodgson J. ADMET-turning chemicals into drugs. Nature Biotechnology. 2001, 19(8): 722-726.
[95] Lewis D.F.V. Human cytochromes P450 associated with the phase 1 metabolism of drugs and other xenobiotics: a compilation of substrates and inhibitors of the CYP1, CYP2 and CYP3 families. Current medicinal chemistry. 2003, 10(19): 1955-1972.
[96] Ingelman-Sundberg M.,Sim S.C. , Gomez A., et al. Influence of cytochrome P450 polymorphisms on drug therapies: pharmacogenetic, pharmacoepigenetic and clinical aspects. Pharmacology & therapeutics. 2007, 116(3): 496-526.
[97] Daly A.K. Pharmacogenetics of the cytochromes P450. Current Topics in Medicinal Chemistry. 2004, 4(16): 1733-1744.
[98] Ding X.,Kaminsky L. Human extrahepatic cytochromes P450: function in xenobiotic metabolism and tissue-selective chemical toxicity in the respiratory and gastrointestinal tracts. Annual review of pharmacology and toxicology. 2003, 43(149-173.
[99] Wang B.,Zhou S.F. Synthetic and natural compounds that interact with human cytochrome P450 1A2 and implications in drug development. Current medicinal chemistry. 2009, 16(31): 4066-4218.
[100] Sansen S.,Yano J.,Reynald R., et al. Adaptations for the oxidation of polycyclic aromatic hydrocarbons exhibited by the structure of human P450 1A2. Journal of Biological Chemistry. 2007, 282(19): 14348-14355.
[101] Cojocaru V.,Winn P.,Wade R. The ins and outs of cytochrome P450s. Biochimica et Biophysica Acta. 2007, 1770(3): 390-401.
[102] Yaffe E.,Fishelovitch D.,Wolfson H.J., et al. MolAxis: Efficient and accurate identification of channels in macromolecules. Proteins: Structure, Function, and Bioinformatics. 2008, 73(1): 72-86.
[103] Behera R.,Mazumdar S. Roles of two surface residues near the access channel in the substrate recognition by cytochrome P450cam. Biophysical chemistry. 2008, 135(1-3): 1-6.
[104] Bechtel S.,Belkina N.,Bernhardt R. The effect of amino‐ acid substitutions I112P, D147E and K152N in CYP11B2 on the catalytic activities of the enzyme. European Journal of Biochemistry. 2002, 269(4): 1118-1127.
[105] Scott E.,He Y.,Halpert J. Substrate Routes to the Buried Active Site May Vary among Cytochromes P450: Mutagenesis of the F- G Region in P450 2B1. Chemical Research in Toxicology. 2002, 15(11): 1407-1413.
[106] Fishelovitch D.,Shaik S.,Wolfson H., et al. How Does the Reductase Help To Regulate the Catalytic Cycle of Cytochrome P450 3A4 Using the Conserved Water Channel? The Journal of Physical Chemistry B. 2010, 114(17): 5964-5970.
[107] Winn P.,Lüdemann S.,Gauges R., et al. Comparison of the dynamics of substrate access channels in three cytochrome P450s reveals different opening mechanisms and a novel functional role for a buried arginine. Proceedings of the National Academy of Sciences of the United States of America. 2002, 99(8): 5361-5366.
[108] Fishelovitch D.,Shaik S.,Wolfson H., et al. Theoretical Characterization of Substrate Access/Exit Channels in the Human Cytochrome P450 3A4 Enzyme: Involvement of Phenylalanine Residues in the Gating Mechanism. The Journal of Physical Chemistry B. 2009, 113(39): 13018-13025.
[109] Wen Z.,Baudry J.,Berenbaum M., et al. Ile115Leu mutation in the SRS1 region of an insect cytochrome P450 (CYP6B1) compromises substrate turnover via changes in a predicted product release channel. Protein Engineering Design and Selection. 2005, 18(4): 191-199.
[110] Zhou H.,Josephy P.,Kim D., et al. Functional characterization of four allelic variants of human cytochrome P450 1A2. Archives of biochemistry and biophysics. 2004, 422(1): 23-30.
[111] Saito Y.,Hanioka N.,Maekawa K., et al. Functional analysis of three CYP1A2 variants found in a Japanese population. Drug Metabolism and Disposition. 2005, 33(12): 1905-1910.
[112] Murayama N.,Soyama A.,Saito Y., et al. Six novel nonsynonymous CYP1A2 gene polymorphisms: catalytic activities of the naturally occurring variant enzymes. Journal of Pharmacology and Experimental Therapeutics. 2004, 308(1): 300-306.
[113] Laskowski R.,Gerick F.,Thornton J. The structural basis of allosteric regulation in proteins. FEBS letters. 2009, 583(11): 1692-1698.
[114] Tsai C.,del Sol A.,Nussinov R. Allostery: absence of a change in shape does not imply that allostery is not at play. Journal of molecular biology. 2008, 378(1): 1-11.
[115] Goodey N.,Benkovic S. Allosteric regulation and catalysis emerge via a common route.Nature Chemical Biology. 2008, 4(8): 474-482.
[116] Ackers G.,Smith F. Effects of site-specific amino acid modification on protein interactions and biological function. Annual Review of Biochemistry. 1985, 54(1): 597-629.
[117] Tousignant A.,Pelletier J. Protein motions promote catalysis. Chemistry & biology. 2004, 11(8): 1037-1042.
[118] Lewis D.,Lake B.,George S., et al. Molecular modelling of CYP1 family enzymes CYP1A1, CYP1A2, CYP1A6 and CYP1B1 based on sequence homology with CYP102. Toxicology. 1999, 139(1-2): 53-79.
[119] Kabsch W.,Sander C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 1983, 22(12): 2577-2637.
[120] Mongan J. Interactive essential dynamics. Journal of Computer-Aided Molecular Design. 2004, 18(6): 433-436.
[121] Humphrey W.,Dalke A.,Schulten K. VMD: visual molecular dynamics. Journal of Molecular Graphics. 1996, 14(1): 33-38.
[122] Hubbard S.,Thornton J. NACCESS computer program. Department of Biochemistry and Molecular Biology, University College London. 1993,
[123] Liang J.,Edelsbrunner H.,Woodward C. Anatomy of protein pockets and cavities: measurement of binding site geometry and implications for ligand design. Protein Science. 1998, 7(1884-1897.
[124] Pet ek M.,Otyepka M.,BanáP., et al. CAVER: a new tool to explore routes from protein clefts, pockets and cavities. BMC bioinformatics. 2006, 7(1): 316-324.
[125] DeLano W. The case for open-source software in drug discovery. Drug Discovery Today. 2005, 10(3): 213-217.
[126] Morris G.,Goodsell D.,Halliday R., et al. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry. 1998, 19(14): 1639-1662.
[127] Totrov M.,Abagyan R. Flexible ligand docking to multiple receptor conformations: a practical alternative. Current opinion in structural biology. 2008, 18(2): 178-184.
[128] Lin J.,Perryman A.,Schames J., et al. Computational drug design accommodating receptor flexibility: the relaxed complex scheme. Journal of the American Chemical Society. 2002, 124(20): 5632-5633.
[129] Thompson J.,Gibson T.,Plewniak F., et al. The CLUSTAL_X windows interface: flexiblestrategies for multiple sequence alignment aided by quality analysis tools. Nucleic acids research. 1997, 25(24): 4876-4882.
[130] Gouet P.,Courcelle E.,Stuart D. ESPript: analysis of multiple sequence alignments in PostScript. Bioinformatics. 1999, 15(4): 305-308.
[131] Achary M.,Nagarajaram H. Effects of disease causing mutations on the essential motions in proteins. Journal of biomolecular structure & dynamics. 2009, 26(5): 609-624.
[132] Daily M.,Gray J. Local motions in a benchmark of allosteric proteins. Proteins: Structure, Function, and Bioinformatics. 2007, 67(2): 385-399.
[133] Rydberg P.,Rod T.,Olsen L., et al. Dynamics of water molecules in the active-site cavity of human cytochromes P450. The Journal of Physical Chemistry. B. 2007, 111(19): 5445-5457.
[134] Lee Y.,Wilson R.,Rupniewski I., et al. P450cam Visits an Open Conformation in the Absence of Substrate. Biochemistry. 2010, 49(16): 3412-3419.
[135] Bauer E.,Guo Z.,Ueng Y., et al. Oxidation of benzo pyrene by recombinant human cytochrome P450 enzymes. Chemical Research in Toxicology. 1995, 8(1): 136-142.
[136] Zhou S.,Yang L.,Zhou Z., et al. Insights into the substrate specificity, inhibitors, regulation, and polymorphisms and the clinical impact of human cytochrome P450 1A2. The AAPS journal. 2009, 11(3): 481-494.
[137] Puchkaev A.V.,Koo L.S.,Ortiz de Montellano P.R. Aromatic stacking as a determinant of the thermal stability of CYP119 from Sulfolobus solfataricus. Archives of Biochemistry and Biophysics. 2003, 409(1): 52-58.
[138] Cui Q.,Karplus M. Allostery and cooperativity revisited. Protein Science. 2008, 17(8): 1295-1307.
[139] del Sol A.,Tsai C.,Ma B., et al. The origin of allosteric functional modulation: multiple pre-existing pathways. Structure. 2009, 17(8): 1042-1050.
[1] Mitchell T.M. Machine learning and data mining. Communications of the ACM. 1999, 42(11): 30-36.
[2] Bishop C.M. Pattern recognition and machine learning. New York: Springer 2006: 7.
[3]陈凯,朱钰.机器学习及其相关算法综述.统计与信息论坛. 2007, 22(005): 105-112.
[4] Kotsiantis S.,Zaharakis I.,Pintelas P. Machine learning: a review of classification and combining techniques. Artificial Intelligence Review. 2006, 26(3): 159-190.
[5] Barlow H.B. Unsupervised learning. Neural Computation. 1989, 1(3): 295-311.
[6] Love B.C. Comparing supervised and unsupervised category learning. Psychonomic Bulletin & Review. 2002, 9(4): 829-835.
[7] Board R.,Pitt L. Semi-supervised learning. Machine Learning. 1989, 4(1): 41-65.
[8] Chapelle O.,Scholkopf B.,Zien A. Semi-supervised learning. London: The MIT Press. 2006: 1-8.
[9] Tan A.C.,Naiman D.Q.,Xu L., et al. Simple decision rules for classifying human cancers from gene expression profiles. Bioinformatics. 2005, 21(20): 3896-3904.
[10] Selbig J.,Mevissen T.,Lengauer T. Decision tree-based formation of consensus protein secondary structure prediction. Bioinformatics. 1999, 15(12): 1039-1046.
[11] Barlow T.,Neville P., Case study: visualization for decision tree analysis in data mining,in. 2001: Published by the IEEE Computer Society.
[12] Mitchell T.M. Machine learning. New York: McGraw Hill. 1997: 52-78.
[13] Takimoto E.,Maruoka A. Top-down decision tree learning as information based boosting. Theoretical Computer Science. 2003, 292(2): 447-464.
[14] Muharram M.A.,Smith G.D. Evolutionary feature construction using information gain and gini index. Genetic Programming. 2004, 379-388.
[15] Quinlan J.R. Induction of decision trees. Machine Learning. 1986, 1(1): 81-106.
[16] Wang J.,Cui J.,Zhao K. Investigation on AQ11, ID3 and the principle of discernibility matrix. Journal of Computer Science and Technology. 2001, 16(1): 1-12.
[17] Markou M.,Singh S. Novelty detection: a review--part 2::: neural network based approaches. Signal Processing. 2003, 83(12): 2499-2521.
[18] KurkováV. Kolmogorov's theorem and multilayer neural networks. Neural Networks. 1992, 5(3): 501-506.
[19]阎平凡,张长水.人工神经网络与模拟进化计算.北京:清华大学出版社. 2000: 60-96.
[20]郭秀娟.数据挖掘方法综述.吉林建筑工程学院学报. 2004, 21(1): 49-53.
[21] Ilonen J.,Kamarainen J.K.,Lampinen J. Differential evolution training algorithm for feed-forward neural networks. Neural Processing Letters. 2003, 17(1): 93-105.
[22] Rumelhart D.E.,Hintont G.E.,Williams R.J. Learning representations by back-propagating errors. Nature. 1986, 323(6088): 533-536.
[23]李翱翔,陈健. BP神经网络参数改进方法综述.数字通信世界. 2009, (001): 62-64.
[24] Kawato M. Feedback-error-learning neural network for supervised motor learning. Advanced neural computers. 1990, 6(3): 365-372.
[25] Kohonen T. The self-organizing map. Proceedings of the IEEE. 1990, 78(9): 1464-1480.
[26]涂晓芝,颜学峰,钱锋.自组织映射网络及其在化学化工领域中的应用进展.计算与应用化学. 2005, 22(9): 737-744.
[27] Holland J.H. Adaptation in natural and artificial systems. Ann Arbor: University of Michigan Press. 1975:
[28] rey Horn J.,Nafpliotis N.,Goldberg D.E. Multiobjective optimization using the niched pareto genetic algorithm. Urbana. 1993, 5161801-2996.
[29] Whitley D. A genetic algorithm tutorial. Statistics and computing. 1994, 4(2): 65-85.
[30] Manderick B.,de Weger M.,Spiessens P., The genetic algorithm and the structure of the fitness landscape,in. 1991: Morgan Kaufmann Publishers.
[31]王小平,曹立明.遗传算法:理论,应用及软件实现.西安:西安交通大学出版社. 2002: 18-50.
[32]陈有青,徐蔡星,钟文亮, et al.一种改进选择算子的遗传算法.计算机工程与应用. 2008, 44(2): 44-50.
[33] Goldberg D.E.,Deb K. A comparative analysis of selection schemes used in genetic algorithms. Foundations of genetic algorithms. 1991, 169-93.
[34] Poon P.W.,Carter J.N. Genetic algorithm crossover operators for ordering applications. Computers & Operations Research. 1995, 22(1): 135-147.
[35] Srinivas M.,Patnaik L.M. Adaptive probabilities of crossover and mutation in genetic algorithms. Systems, Man and Cybernetics, IEEE Transactions on. 1994, 24(4): 656-667.
[36] Baranczewski P.,Stanczak A.,Sundberg K., et al. Introduction to in vitro estimation ofmetabolic stability and drug interactions of new chemical entities in drug discovery and development. Pharmacol Rep. 2006, 58(4): 453-472.
[37] Burton J.,Ijjaali I.,Petitet F., et al. Virtual screening for cytochromes P450: successes of machine learning filters. Combinatorial Chemistry &# 38; High Throughput Screening. 2009, 12(4): 369-382.
[38] Sun H.,Scott D.O. Structure‐ based Drug Metabolism Predictions for Drug Design. Chemical Biology & Drug Design. 2010, 75(1): 3-17.
[39] Madden J.C.,Cronin M.T.D. Structure-based methods for the prediction of drug metabolism. Expert Opinion on Drug Metabolism & Toxicology. 2006, 2(4): 545-557.
[40] Fox T.,Kriegl J.M. Machine learning techniques for in silico modeling of drug metabolism. Current Topics in Medicinal Chemistry. 2006, 6(15): 1579-1591.
[41] Korolev D.,Balakin K.V.,Nikolsky Y., et al. Modeling of human cytochrome P450-mediated drug metabolism using unsupervised machine learning approach. Journal of medicinal chemistry. 2003, 46(17): 3631-3643.
[42] Zhang H.,Singer B. Recursive partitioning in the health sciences. New York: Springer Verlag. 1999: 7-16.
[43] Feng J.,Lurati L.,Ouyang H., et al. Predictive toxicology: benchmarking molecular descriptors and statistical methods. Journal of chemical information and computer sciences. 2003, 43(5): 1463-1470.
[44] Rusinko III A.,Farmen M.W.,Lambert C.G., et al. Analysis of a Large Structure/Biological Activity Data Set Using Recursive Partitioning 1. Journal of chemical information and computer sciences. 1999, 39(6): 1017-1026.
[45] van Rhee A.M.,Stocker J.,Printzenhoff D., et al. Retrospective analysis of an experimental high-throughput screening data set by recursive partitioning. Journal of Combinatorial Chemistry. 2001, 3(3): 267-277.
[46] Ekins S.,Berbaum J.,Harrison R.K. Generation and validation of rapid computational filters for CYP2D6 and CYP3A4. Drug metabolism and disposition. 2003, 31(9): 1077-1080.
[47] Ekins S. In silico approaches to predicting drug metabolism, toxicology and beyond. Biochemical Society Transactions. 2003, 31(3): 611-614.
[48] Dixon S.L.,Villar H.O. Investigation of classification methods for the prediction of activity in diverse chemical libraries. Journal of computer-aided molecular design. 1999, 13(5): 533-545.
[49] Susnow R.G.,Dixon S.L. Use of robust classification techniques for the prediction of humancytochrome P450 2D6 inhibition. Journal of chemical information and computer sciences. 2003, 43(4): 1308-1315.
[50] Hudelson M.G.,Jones J.P. Line-walking method for predicting the inhibition of p450 drug metabolism. Journal of medicinal chemistry. 2006, 49(14): 4367-4373.
[51] Yap C.W.,Chen Y.Z. Prediction of cytochrome P450 3A4, 2D6, and 2C9 inhibitors and substrates by using support vector machines. Journal of chemical information and modeling. 2005, 45(4): 982-992.
[52] Burton J.,Ijjaali I.,Barberan O., et al. Recursive partitioning for the prediction of cytochromes P450 2D6 and 1A2 inhibition: importance of the quality of the dataset. Journal of medicinal chemistry. 2006, 49(21): 6231-6240.
[53] Chohan K.K.,Paine S.W.,Mistry J., et al. A rapid computational filter for cytochrome P450 1A2 inhibition potential of compound libraries. Journal of medicinal chemistry. 2005, 48(16): 5154-5161.
[54] Arimoto R.,Prasad M.A.,Gifford E.M. Development of CYP3A4 inhibition models: comparisons of machine-learning techniques and molecular descriptors. Journal of biomolecular screening. 2005, 10(3): 197-205.
[55] Zupan J.,Gasteiger J. Neural networks in chemistry and drug design. Weinheim: Vch Verlagsgesellschaft Mbh. 1999: 157-172.
[56] Maniyar D.M.,Nabney I.T.,Williams B.S., et al. Data visualization during the early stages of drug discovery. Journal of chemical information and modeling. 2006, 46(4): 1806-1818.
[57] Burden F.R.,Winkler D.A.,Polley M.J. Predictive human intestinal absorption QSAR models using Bayesian regularized neural networks. Australian journal of chemistry. 2005, 58(12): 859-863.
[58] Winkler D.A. Neural networks as robust tools in drug lead discovery and development. Molecular biotechnology. 2004, 27(2): 139-167.
[59] Molnár L.,Keser G.M. A neural network based virtual screening of cytochrome P450 3A4 inhibitors. Bioorganic & medicinal chemistry letters. 2002, 12(3): 419-421.
[60] Balakin K.V.,Ekins S.,Bugrim A., et al. Kohonen maps for prediction of binding to human cytochrome P450 3A4. Drug metabolism and disposition. 2004, 32(10): 1183-1189.
[61] Sean E.O.B.,de Groot M.J. Greater than the sum of its parts: combining models for useful ADMET prediction. Journal of medicinal chemistry. 2005, 48(4): 1287-1291.
[62] Wang Y.H.,Li Y.,Li Y.H., et al. Modeling Km values using electrotopological state: substratesfor cytochrome P450 3A4-mediated metabolism. Bioorganic & medicinal chemistry letters. 2005, 15(18): 4076-4084.
[63] Lewis D.F.V. 57 varieties: the human cytochromes P450. Parmacogenomics. 2004, 5(3): 305-318.
[64] Feiters M.C.,Rowan A.E.,Nolte R.J.M. From simple to supramolecular cytochrome P450 mimics. Chemical Society Reviews. 2000, 29(6): 375-384.
[65] Nelson D.R.,Kamataki T.,Waxman D.J., et al. The P450 superfamily: update on new sequences, gene mapping, accession numbers, early trivial names of enzymes, and nomenclature. DNA and Cell Biology. 1993, 12(1): 1-51.
[66] Nelson D.R. Cytochrome P450 Nomenclature, 2004. Methods in Molecular Biology 2006, 3201-10.
[67] Lewis D.F.V.,Ito Y. Cytochrome P450 Structure and Function: An Evolutionary Perspective. Cambridge, UK.: Royal Society of Chemistry. 2008: 4-39.
[68] Guengerich F.P. Cytochromes P450, drugs, and diseases. Molecular Interventions. 2003, 3(4): 194-204.
[69] Evans W.E.,Relling M.V. Pharmacogenomics: translating functional genomics into rational therapeutics. Science. 1999, 286(5439): 487-491.
[70] Patterson L.H. , Murray G.I. Tumour cytochrome P450 and drug activation. Current pharmaceutical design. 2002, 8(15): 1335-1347.
[71] Brown C.M.,Reisfeld B.,Mayeno A.N. Cytochromes P450: a structure-based summary of biotransformations using representative substrates. Drug metabolism reviews. 2008, 40(1): 1-100.
[72] Veith H.,Southall N.,Huang R., et al. Comprehensive characterization of cytochrome P450 isozyme selectivity across chemical libraries. Nature biotechnology. 2009, 27(11): 1050-1055.
[73] Lewis D.F.V. Molecular modeling of human cytochrome P450-substrate interactions. Drug metabolism reviews. 2002, 34(1-2): 55-67.
[74] Ito Y.,Kondo H.,Goldfarb P.S., et al. Analysis of CYP2D6 substrate interactions by computational methods. Journal of Molecular Graphics and Modelling. 2008, 26(6): 947-956.
[75] Park H.,Lee S.,Suh J. Structural and dynamical basis of broad substrate specificity, catalytic mechanism, and inhibition of cytochrome P450 3A4. J. Am. Chem. Soc. 2005, 127(39): 13634-13642.
[76] Seifert A.,Tatzel S.,Schmid R.D., et al. Multiple molecular dynamics simulations of humanp450 monooxygenase CYP2C9: the molecular basis of substrate binding and regioselectivity toward warfarin. Proteins: Structure, Function, and Bioinformatics. 2006, 64(1): 147-155.
[77] Ekins S.,de Groot M.J.,Jones J.P. Pharmacophore and three-dimensional quantitative structure activity relationship methods for modeling cytochrome P450 active sites. Drug metabolism and disposition. 2001, 29(7): 936-944.
[78] de Groot M.J.,Ekins S. Pharmacophore modeling of cytochromes P450. Advanced drug delivery reviews. 2002, 54(3): 367-383.
[79] Ekins S.,Stresser D.M.,Andrew Williams J. In vitro and pharmacophore insights into CYP3A enzymes. Trends in pharmacological sciences. 2003, 24(4): 161-166.
[80] Friesner R.A. , Guallar V. Ab initio quantum chemical and mixed quantum mechanics/molecular mechanics (QM/MM) methods for studying enzymatic catalysis. Physical Chemistry. 2005, 56(1): 389-427.
[81] Bathelt C.M.,Zurek J.,Mulholland A.J., et al. Electronic structure of compound I in human isoforms of cytochrome P450 from QM/MM modeling. J. Am. Chem. Soc. 2005, 127(37): 12900-12908.
[82] Crivori P.,Poggesi I. Computational approaches predicting CYP-related metabolism properties in the screening of new drugs. European journal of medicinal chemistry. 2006, 41(7): 795-808.
[83] Xie Z.,Zhang T.,Wang J.F., et al. The computational model to predict accurately inhibitory activity for inhibitors towardsCYP3A4. Computers in Biology and Medicine. 2010, 40(11-12): 845-852.
[84] Michielan L.,Terfloth L.,Gasteiger J., et al. Comparison of Multilabel and Single-Label Classification Applied to the Prediction of the Isoform Specificity of Cytochrome P450 Substrates. Journal of chemical information and modeling. 2009, 49(11): 2588-2605.
[85] Guengerich F.P. Cytochrome P-450 3A4: regulation and role in drug metabolism. Annual review of pharmacology and toxicology. 1999, 391-17.
[86] Wishart D.S.,Knox C.,Guo A.C., et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic acids research. 2008, 36(suppl 1): D901-D906.
[87] Halgren T.A. Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry. 1996, 17(5-6): 490-519.
[88] Stewart J.J.P. MOPAC: a semiempirical molecular orbital program. Journal of Computer-Aided Molecular Design. 1990, 4(1): 1-103.
[89] Pallas (version 1.2 for Windows) distributed by Compu Drug Chemistry Ltd.
[90] Frank E.,Hall M.,Trigg L., et al. Data mining in bioinformatics using Weka. Bioinformatics. 2004, 20(15): 2479-2481.
[91] Witten I.H.,Frank E. Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann Pub. 2005:
[92] Guyon I.,Elisseeff A. An introduction to variable and feature selection. The Journal of Machine Learning Research. 2003, 31157-1182.
[93] Ou G.,Murphey Y.L. Multi-class pattern classification using neural networks. Pattern Recognition. 2007, 40(1): 4-18.
[94] Hirose Y.,Yamashita K.,Hijiya S. Back-propagation algorithm which varies the number of hidden units. Neural Networks. 1991, 4(1): 61-66.
[95] Zhang M.L.,Zhou Z.H., A k-nearest neighbor based algorithm for multi-label classification,in. 2005: IEEE.
[96] Gersmann K.,Hammer B. Improving iterative repair strategies for scheduling with the SVM. Neurocomputing. 2005, 63271-292.
[97] Hristozov D.,Gasteiger J.,Da Costa F.B. Multilabeled classification approach to find a plant source for terpenoids. J. Chem. Inf. Model. 2008, 48(1): 56-67.
[98] Safavian S.R.,Landgrebe D. A survey of decision tree classifier methodology. Systems, Man and Cybernetics, IEEE Transactions on. 2002, 21(3): 660-674.
[99] Zhao Y.,Zhang Y. Comparison of decision tree methods for finding active objects. Advances in Space Research. 2008, 41(12): 1955-1959.
[100] Williams P.A.,Cosme J.,Ward A., et al. Crystal structure of human cytochrome P450 2C9 with bound warfarin. Nature. 2003, 424(6497): 464-468.
[101] Williams P.A.,Cosme J.,Vinkovic D.M., et al. Crystal structures of human cytochrome P450 3A4 bound to metyrapone and progesterone. Science. 2004, 305(5684): 683-686.
[102] Sevrioukova I.F.,Poulos T.L. Structure and mechanism of the complex between cytochrome P4503A4 and ritonavir. Proceedings of the National Academy of Sciences. 2010, 107(43): 18422-18427.
[103] Sansen S.,Yano J.K.,Reynald R.L., et al. Adaptations for the oxidation of polycyclic aromatic hydrocarbons exhibited by the structure of human P450 1A2. Journal of Biological Chemistry. 2007, 282(19): 14348-14355.
[104] Tsoumakas G.,Katakis I. Multi-label classification: An overview. International Journal of Data Warehousing and Mining. 2007, 3(3): 1-13.
[105] McCallum A.K., Multi-label text classification with a mixture model trained by EM,in AAAI99 Workshop on Text Learing. 1999: Citeseer.
[106] Boutell M.R.,Luo J.,Shen X., et al. Learning multi-label scene classification. Pattern Recognition. 2004, 37(9): 1757-1771.
[107] Diplaris S.,Tsoumakas G.,Mitkas P., et al. Protein classification with multiple algorithms. Advances in Informatics. 2005, 3746448-456.
[108] Clare A.,King R. Predicting gene function in Saccharomyces cerevisiae. Bioinformatics. 2003, 19(suppl 2): 42-49.
[1]安丽英,相玉红,张卓勇, et al.定量构效关系研究进展及其应用.首都师范大学学报:自然科学版. 2006, 27(3): 52-57.
[2] Martin B.R. Cellular effects of cannabinoids. Pharmacological Reviews. 1986, 38(1): 45-74.
[3] Hansch C.,Muir R.M.,Fujita T., et al. The correlation of biological activity of plant growth regulators and chloromycetin derivatives with Hammett constants and partition coefficients. Journal of the American Chemical Society. 1963, 85(18): 2817-2824.
[4] Hansch C. Quantitative structure-activity relationships in drug design. New York: Academic Press. 1971:
[5]于瑞莲,胡恭任.环境化学中有机化合物毒性的QSAR研究方法.环境科学与技术. 2003, 26(1): 57-59.
[6] Yang G.F.,Huang X. Development of quantitative structure-activity relationships and its application in rational drug design. Current Pharmaceutical Design. 2006, 12(35): 4601-4611.
[7] Kubinyi H. QSAR: Hansch analysis and related approaches. New York: VCH Publisher. 1993: 57-85.
[8] Marshall G.R. Computer-aided drug design. Annual Review of Pharmacology and Toxicology. 1987, 27(1): 193-213.
[9] Topliss J.G. A manual method for applying the Hansch approach to drug design. Journal of Medicinal Chemistry. 1977, 20(4): 463-469.
[10] Free S.M.,Wilson J.W. A mathematical contribution to structure-activity studies. Journal of Medicinal Chemistry. 1964, 7(4): 395-399.
[11] Valkenburg W.V. Biological Correlations-The Hansch Approach. Washington D.C American Chemical Society. 1975: 115-129.
[12] Kier L.B.,Hall L.H. Intermolecular accessibility: the meaning of molecular connectivity. Journal of Chemical Information and Computer Sciences. 2000, 40(3): 792-795.
[13] Sanz F.,López de Brias E.,Rodríguez J., et al. Theoretical Study on the Metabolism of Caffeine by Cytochrome P‐ 450 1A2 and its Inhibition. Quantitative Structure‐ Activity Relationships. 1994, 13(3): 281-284.
[14] Fuhr U.,Strobl G.,Manaut F., et al. Quinolone antibacterial agents: relationship betweenstructure and in vitro inhibition of the human cytochrome P450 isoform CYP1A2. Molecular Pharmacology. 1993, 43(2): 191-199.
[15] Lee H.,Yeom H.,Kim Y.G., et al. Structure-related inhibition of human hepatic caffeine N3-demethylation by naturally occurring flavonoids. Biochemical Pharmacology. 1998, 55(9): 1369-1375.
[16] Kubinyi H. QSAR and 3D QSAR in drug design Part 1: methodology. Drug Discovery Today. 1997, 2(11): 457-467.
[17] Hopfinger A.J. A QSAR investigation of dihydrofolate reductase inhibition by Baker triazines based upon molecular shape analysis. Journal of the American Chemical Society. 1980, 102(24): 7196-7206.
[18] Crippen G.M. Quantitative structure-activity relationships by distance geometry: thyroxine binding site. Journal of Medicinal Chemistry. 1981, 24(2): 198-203.
[19] Klebe G.,Abraham U.,Mietzner T. Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. Journal of Medicinal Chemistry. 1994, 37(24): 4130-4146.
[20] Ruan Z.,Wang H.,Ren Y., et al. Pseudo receptor probes: A novel pseudo receptor-based QSAR method and application into studies on a new kind of selective vascular endothelial growth factor-2 receptor inhibitors. Chemometrics and Intelligent Laboratory Systems. 2008, 92(2): 157-168.
[21] Cramer III R.D.,Patterson D.E.,Bunce J.D. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. Journal of the American Chemical Society. 1988, 110(18): 5959-5967.
[22]侯廷军,徐筱杰.比较分子场分析方法研究的最新进展化学进展. 2001, 13(6): 436-440.
[23] De Groot M.J. Designing better drugs: predicting cytochrome P450 metabolism. Drug Discovery Today. 2006, 11(13-14): 601-606.
[24] Lozano J.J.,Pastor M.,Cruciani G., et al. 3D-QSAR methods on the basis of ligand–receptor complexes. Application of COMBINE and GRID/GOLPE methodologies to a series of CYP1A2 ligands. Journal of Computer-Aided Molecular Design. 2000, 14(4): 341-353.
[25] Poso A.,Gynther J.,Juvonen R. A comparative molecular field analysis of cytochrome P450 2A5 and 2A6 inhibitors. Journal of Computer-Aided Molecular Design. 2001, 15(3): 195-202.
[26] Ekins S.,Bravi G.,Ring B.J., et al. Three-dimensional quantitative structure activity relationship analyses of substrates for CYP2B6. Journal of Pharmacology and ExperimentalTherapeutics. 1999, 288(1): 21-29.
[27] Jones J.P.,He M.,Trager W.F., et al. Three-dimensional quantitative structure-activity relationship for inhibitors of cytochrome P4502C9. Drug Metabolism and Disposition. 1996, 24(1): 1-6.
[28] Afzelius L.,Zamora I.,Masimirembwa C.M., et al. Conformer-and alignment-independent model for predicting structurally diverse competitive CYP2C9 inhibitors. Journal of Medicinal Chemistry. 2004, 47(4): 907-914.
[29] Locuson C.W.,Rock D.A.,Jones J.P. Quantitative Binding Models for CYP2C9 Based on Benzbromarone Analogues. Biochemistry. 2004, 43(6948-6958.
[30] Schneider G.,Coassolo P.,LavéT. Combining in vitro and in vivo pharmacokinetic data for prediction of hepatic drug clearance in humans by artificial neural networks and multivariate statistical techniques. Journal of Medicinal Chemistry. 1999, 42(25): 5072-5076.
[31] Lee S.,Kim D. Equation chapter 1 section 1A new method for predicting human hepatic clearance from in vitro experimental data using molecular descriptors. Archives of Pharmacal Research. 2007, 30(2): 182-190.
[32] Lee P.H.,Cucurull-Sanchez L.,Lu J., et al. Development of in silico models for human liver microsomal stability. Journal of Computer-Aided Molecular Design. 2007, 21(12): 665-673.
[33] Chohan K.K.,Paine S.W.,Mistry J., et al. A rapid computational filter for cytochrome P450 1A2 inhibition potential of compound libraries. Journal of Medicinal Chemistry. 2005, 48(16): 5154-5161.
[34] Burton J.,Ijjaali I.,Barberan O., et al. Recursive partitioning for the prediction of cytochromes P450 2D6 and 1A2 inhibition: importance of the quality of the dataset. Journal of Medicinal Chemistry. 2006, 49(21): 6231-6240.
[35] Kriegl J.M.,Arnhold T.,Beck B., et al. Prediction of human cytochrome P450 inhibition using support vector machines. QSAR & Combinatorial Science. 2005, 24(4): 491-502.
[36] Li H.,Sun J.,Fan X., et al. Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction. Journal of Computer-Aided Molecular Design. 2008, 22(11): 843-855.
[37] Elbekai R.H.,El-Kadi A.O.S. Cytochrome P450 enzymes: central players in cardiovascular health and disease. Pharmacology & Therapeutics. 2006, 112(2): 564-587.
[38] Rushmore T.H.,Tony K.A. Pharmacogenomics, regulation and signaling pathways of phase I and II drug metabolizing enzymes. Current Drug Metabolism. 2002, 3(5): 481-490.
[39] Coon M.J.,Strobel H.W.,Boyer R.F. On the mechanism of hydroxylation reactions catalyzed by cytochrome P-450. Drug Metabolism and Disposition. 1973, 1(1): 92-97.
[40] Shaik S.,Kumar D.,de Visser S.P., et al. Theoretical perspective on the structure and mechanism of cytochrome P450 enzymes. Chemical Reviews. 2005, 105(6): 2279-2328.
[41] Lewis D.F.V.,Pratt J.M. The P 450 catalytic cycle and oxygenation mechanism. Drug Metabolism Reviews. 1998, 30(4): 739-786.
[42] Meunier B.,De Visser S.P.,Shaik S. Mechanism of oxidation reactions catalyzed by cytochrome P450 enzymes. Chemical Reviews. 2004, 104(9): 3947-3980.
[43] Werck-Reichhart D.,Feyereisen R. Cytochromes P450: a success story. Genome Biol. 2000, 1(6): 1-9.
[44] Denisov I.G.,Makris T.M.,Sligar S.G., et al. Structure and chemistry of cytochrome P450. Chemical Reviews. 2005, 105(6): 2253-2278.
[45] Hays A.M.A.,Dunn A.R.,Chiu R., et al. Conformational states of cytochrome P450cam revealed by trapping of synthetic molecular wires. Journal of Molecular Biology. 2004, 344(2): 455-469.
[46] Cojocaru V.,Winn P.J.,Wade R.C. The ins and outs of cytochrome P450s. Biochimica et Biophysica Acta (BBA)-General Subjects. 2007, 1770(3): 390-401.
[47] Rydberg P.,Rod T.H.,Olsen L., et al. Dynamics of water molecules in the active-site cavity of human cytochromes P450. The Journal of Physical Chemistry B. 2007, 111(19): 5445-5457.
[48] Williams P.A.,Cosme J.,Ward A., et al. Crystal structure of human cytochrome P450 2C9 with bound warfarin. Nature. 2003, 424(6947): 464-468.
[49] Wester M.R.,Yano J.K.,Schoch G.A., et al. The structure of human cytochrome P450 2C9 complexed with flurbiprofen at 2.0-resolution. Journal of Biological Chemistry. 2004, 279(34): 35630-35637.
[50] Rowland P.,Blaney F.E.,Smyth M.G., et al. Crystal structure of human cytochrome P450 2D6. Journal of Biological Chemistry. 2006, 281(11): 7614-7622.
[51] Ito Y.,Kondo H.,Goldfarb P.S., et al. Analysis of CYP2D6 substrate interactions by computational methods. Journal of Molecular Graphics and Modelling. 2008, 26(6): 947-956.
[52] Sun H.,Scott D.O. Structure‐ based Drug Metabolism Predictions for Drug Design. Chemical Biology & Drug Design. 2010, 75(1): 3-17.
[53] de Groot M.J.,Ackland M.J.,Horne V.A., et al. Novel approach to predicting P450-mediated drug metabolism: development of a combined protein and pharmacophore model for CYP2D6.Journal of Medicinal Chemistry. 1999, 42(9): 1515-1524.
[54] de Groot M.J.,Ekins S. Pharmacophore modeling of cytochromes P450. Advanced Drug Delivery Reviews. 2002, 54(3): 367-383.
[55] Freitas R.,Bauab R.,Montanari C. Novel Application of 2D and 3D-Similarity Searches To Identify Substrates among Cytochrome P450 2C9, 2D6, and 3A4. Journal of Chemical Information and Modeling. 2010, 50(1): 97-109.
[56] Gunes A.,Dahl M.L. Variation in CYP1A2 activity and its clinical implications: influence of environmental factors and genetic polymorphisms. Pharmacogenomics. 2008, 9(5): 625-637.
[57] Wang B.,Zhou S.F. Synthetic and natural compounds that interact with human cytochrome P450 1A2 and implications in drug development. Current Medicinal Chemistry. 2009, 16(31): 4066-4218.
[58] Sansen S.,Yano J.K.,Reynald R.L., et al. Adaptations for the oxidation of polycyclic aromatic hydrocarbons exhibited by the structure of human P450 1A2. Journal of Biological Chemistry. 2007, 282(19): 14348-14355.
[59] Lewis D.F.V.,Ito Y. Human CYPs involved in drug metabolism: structures, substrates and binding affinities. Expert Opinion on Drug Metabolism & Toxicology. 2010, 6(6): 661-674.
[60] Rendic S. Summary of information on human CYP enzymes: human P450 metabolism data. Drug Metabolism Reviews. 2002, 34(1-2): 83-448.
[61] Halgren T.A. Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry. 1996, 17(5-6): 490-519.
[62] Case D.,Darden T.,Cheatham III T., et al. AMBER 8. University of California, San Francisco. 2004,
[63] Huey R.,Morris G.M.,Olson A.J., et al. A semiempirical free energy force field with charge‐ based desolvation. Journal of Computational Chemistry. 2007, 28(6): 1145-1152.
[64] Schames J.,Henchman R.,Siegel J., et al. Discovery of a novel binding trench in HIV integrase. J. Med. Chem. 2004, 47(8): 1879-1881.
[65] Lin J.,Perryman A.,Schames J., et al. Computational drug design accommodating receptor flexibility: the relaxed complex scheme. J. Am. Chem. Soc. 2002, 124(20): 5632-5633.
[66] Efron B. Bootstrap methods: another look at the jackknife. The Annals of Statistics. 1979, 7(1): 1-26.
[67] Lewis D.,Ito Y. Human P450s involved in drug metabolism and the use of structural modelling for understanding substrate selectivity and binding affinity. Xenobiotica. 2009,39(8): 625-635.
[68] Kumar G.N.,Surapaneni S. Role of drug metabolism in drug discovery and development. Medicinal Research Reviews. 2001, 21(5): 397-411.
[69] Parikh A. , Josephy P.D. , Guengerich F.P. Selection and Characterization of Human Cytochrome P450 1A2 Mutants with Altered Catalytic Properties. Biochemistry. 1999, 38(17): 5283-5289.
[70] Hutchison C.A.,Phillips S.,Edgell M., et al. Mutagenesis at a specific position in a DNA sequence. Journal of Biological Chemistry. 1978, 253(18): 6551-6560.
[71] Liu J.,Ericksen S.S.,Sivaneri M., et al. The effect of reciprocal active site mutations in human cytochromes P450 1A1 and 1A2 on alkoxyresorufin metabolism. Archives of Biochemistry and Biophysics. 2004, 424(1): 33-43.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |