Efficient Strategies for Lead Optimization by Simultaneously Addressing Affinity, Selectivity and Pharmacokinetic Parameters

Chemoinformatics in Drug Discovery

Volumn 23, Issue , 2005, Pages 333-379

  Baringhaus, Karl Heinz ^a   Matter, Hans ^a  

^a SANOFI AVENTIS DEUTSCHLAND GMBH   (Germany)

Author keywords

Addressing pharmacokinetic problems; ADME antitarget models for lead optimization; Efficient strategies for lead optimization; Integrated approach; Optimization for affinity and selectivity; Origin of lead structures

Indexed keywords

BIOCHEMISTRY; FORECASTING; INTEGRATED CONTROL; LIGANDS; PHARMACOKINETICS; RISK ASSESSMENT; SHAPE OPTIMIZATION; STRUCTURAL DESIGN;

ADDRESSING PHARMACOKINETIC PROBLEMS; INTEGRATED APPROACH; LEAD OPTIMIZATION; LEAD STRUCTURE; MULTIDIMENSIONAL OPTIMIZATION; PHARMACOKINETIC PARAMETERS; PHYSICOCHEMICAL PROPERTY; STRUCTURE-BASED DESIGNS;

STRUCTURAL OPTIMIZATION;

EID: 85016037985     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/3527603743.ch14     Document Type: Chapter

References (219)

1. LLOYD, A. Modifying the drug discovery/drug development paradigm. Drug Disc. Today 1997, 2, 397-398.
2. WESS, G., URMANN, M., and SICKENBERGER, B. Medicinal chemistry: challenges and opportunities. Angew. Chem., Int. Ed. Engl. 2001, 40, 3341-3350.
3. WESS, G. How to escape the bottleneck of medicinal chemistry. Drug Disc. Today 2002, 7, 533-535.
4. LAWRENCE, R.N. Sir Richard Sykes contemplates the future of the pharma industry. Drug Disc. Today 2002, 7, 645-648.
5. SHAH, N.D., VERMEULEN, L.C., SANTELL, J.P., HUNKLER, R.J., and HONTZ, K. Projecting future drug expenditures-2002. Am. J. Health Syst. Pharm. 2002, 59, 131-142.
6. DIMASI, J.A. Risks in new drug development: approval success rates for investigational drugs. Clin. Pharmacol. Ther. 2001, 69, 297-307.
7. PRENTIS, R.A., LIS, Y., and WALKER, S.R. Pharmaceutical innovation by the seven UK-owned pharmaceutical companies (1964-1985). Br. J. Clin. Pharmacol. 1988, 25, 387-396.
8. KENNEDY, T. Managing the drug discovery/development interface. Drug Disc. Today 1997, 2, 436-444.
9. DREWS, J. Drug discovery: a historical perspective. Science 2000, 287, 1960-1964.
10. HILLISCH, A. and HILGENFELD, R. (Eds). Modern Methods of Drug Discovery. Birkhäuser, Basel, 2003.
11. GORDON, E.M. and KERWIN, J.F. (Eds). Combinatorial Chemistry and Molecular Diversity in Drug Discovery. Wiley, New York, USA, 1998
12. JUNG, G. (Ed.). Combinatorial Chemistry. Wiley-VCH, Weinheim, 1999.
13. ALLOP, M.A., BARRETT, R.W., DOWER, W.J., FODOR, S.P.A., and GORDON, E.M. Applications of combinatorial technologies to drug discovery. 1. Background and peptide combinatorial libraries. J. Med. Chem. 1994, 37, 1233-1251
14. GORDON, E.M., BARRETT, R.W., DOWER, W.J., FODOR, S.P.A., and GALLOP, M.A. Applications of combinatorial technologies to drug discovery. 2. Combinatorial organic synthesis, library screening strategies, and future directions. J. Med. Chem. 1994, 37, 1385-1399
15. MADDEN, D., KRCHNAK, V., and LEBL, M. Synthetic combinatorial libraries: views on techniques and their applications. Perspect. Drug Discov. Des. 1995, 2, 269-285
16. ELLMAN, J.A. Design, synthesis and evaluation of small-molecule libraries. Acc. Chem. Res. 1996, 29, 132-143
17. GORDON, E.M., GALLOP, M.A., and PATEL, D.V. Strategy and tactics in combinatorial organic synthesis. Application to drug discovery. Acc. Chem. Res. 1996, 29, 144-154
18. FRUCHTEL, J.S. and JUNG, G. Organic chemistry on solid supports. Angew. Chem., Int. Ed. Engl. 1996, 35, 17-42
19. THOMPSON, L.A. and ELLMAN, J.A. Synthesis and applications of small molecule libraries. Chem. Rev. 1996, 96, 555-600
20. CHOON, I.C. and ELLMAN, J.A. Solid-phase synthesis: applications to combinatorial libraries. Annu. Rep. Med. Chem. 1996, 31, 309-318
21. BALKENHOHL, F., VON DEM BUSSCHEHÜNNEFELD, C., LANSKY, A., and ZECHEL, C. Combinatorial synthesis of small organic molecules. Angew. Chem., Int. Ed. Engl. 1996, 35, 2288-2337
22. NEFZI, A., OSTRESH, J.M., and HOUGHTEN, R.A. The current status of heterocyclic combinatorial libraries. Chem. Rev. 1997, 97, 449-472
23. BRISTOL, J.A. (Ed.). Applications of solid-supported organic synthesis in combinatorial chemistry. Tetrahedron 1997, 53, 6573-6706
24. GEYSEN, H.M., SCHOENEN, F., WAGNER, D., and WAGNER, R. Combinatorial compound libraries for drug discovery: an ongoing challenge. Nat. Rev. Drug Disc. 2003, 2, 222-230.
25. LANDRO, J.A., TAYLOR, I.C.A., STIRTAN, W.G., OSTERMAN, D.G., KRISTIE, J., HUNNICUTT, E.J., RAE, P.M.M., and SWEETNAM, P.M. HTS in the new millennium: the role of pharmacology and flexibility. J. Pharm. Toxicol. Methods 2000, 44, 273-289.
26. LAHANA, R. How many leads from HTS? Drug Disc. Today 1999, 4, 447.
27. ZALL, M. The pricing puzzle. Mod. Drug Disc. 2001, 4, 36-38.
28. ALANINE, A., NETTEKOVEN, M., ROBERTS, E., and THOMA, A.W. Lead generation - enhancing the success of drug discovery by investing in the hit to lead process. Comb. Chem. High Throughput Screen. 2003, 6, 51-66.
29. HILL, S.A. Drug Discov. Word Spring 2001, 19-25.
30. BRENNAN, M.B. Chem. Eng. News 2000, 78(26), 63-74.
31. PROUDFOOT, J.R. Drugs, leads, and drug-likeness: an analysis of some recently launched drugs. Bioorg. Med. Chem. Lett. 2002, 12, 1647-1650.
32. OPREA, T. Virtual screening in lead discovery: a viewpoint. Molecules 2002, 7, 51-62.
33. ZAMORA, I., OPREA, T., CRUCIANI, G., PASTOR, M., and UNGELL, A.-L. Surface descriptors for protein-ligand affinity prediction. J. Med. Chem. 2003, 46, 25-33.
34. BLEICHER, K.H., BÖHM, H.J., MÜLLER, K., and ALANINE, A.I. Hit and lead generation: beyond high throughput screening. Nat. Rev. Drug Disc. 2003, 369-378.
35. HODGSON, J. ADMET - turning chemicals into drugs. Nat. Biotechnol. 2001, 19, 722-726.
36. HOPKINS, A.L. and GROOM, C.R. The druggable genome. Nat. Rev. Drug Disc. 2002, 1, 727-730.
37. LIPINSKI, C.A., LOMBARDO, F., DOMINY, B.W., and FEENEY, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 1997, 23, 3-25.
38. VEBER, D.F., JOHNSON, S.R., CHENG, H.Y., SMITH, B.R., WARD, K.W., and KOPPLE, K.D. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem. 2002, 12, 2615-2623.
39. SUNDBERG, S.A. High-throughput and ultra-high-throughput screening: solution- and cell-based approaches. Curr. Opin. Biotechnol. 2000, 11, 47-53.
40. THIERICKE, R. High-throughput screening technologies. In Modern Methods of Drug Discovery, HILLISCH, A. and HILGENFELD, R. (Eds). Birkhäuser, Basel, 2003, 71-85.
41. SHUKER, S.B., HAJDUK, P.J., MEADOWS, R.P., and FESIK, S.W. Discovering high-affinity ligands for proteins: SAR by NMR. Science 1996, 274, 1531-1534.
42. HAJDUK, P.J., BOYD, S., NETTESHEIM, D., NIENABER, V., SEVERIN, J., SMITH, R., DAVIDSON, D., ROCKWAY, T., and FESIK, S.W. Identification of novel inhibitors of urokinase via NMR-based screening. J. Med. Chem. 2000, 43, 3862-3866.
43. FEJZO, J., LEPRE, C.A., PENG, J.W., BEMIS, G.W., AJAY, MURCKO, M.A., and MOORE, J.M. The SHAPES strategy: an NMRbased approach for lead generation in drug discovery. Chem. Biol. 1999, 6, 755-769.
44. KUMAR, S. and GUNNARSSON, K. Small molecule drug screening based on surface plasmon resonance. In Advantages of Drug Discovery Technology, HARVEY, A.L. (Ed.). Wiley, Chichester, UK, 1998, 97-114.
45. NIENABER, V.L., RICHARDSON, P.L., KLIGHOFER, V., BOUSKA, J.J., GIRANDA, V.L., and GREER, J. Discovering novel ligands for macromolecules using X-ray crystallographic screening. Nat. Biotechnol. 2000, 18, 1105-1107.
46. LESUISSE, D., LANGE, G., DEPREZ, P., BENARD, D., SCHOOT, B., DELETTRE, G., MARQUETTE, J.P., BROTO, P., JEAN-BAPTISTE, V., BICHET, P., SARUBBI, E., and MANDINE, E. SAR and X-ray -a new approach combining fragment-based screening and rational drug design: application to the discovery of nanomolar inhibitors of src SH2. J. Med. Chem. 2002, 45, 2379-2387.
47. STAHL, M., TODOROV, N.P., JAMES, T., MAUSER, H., BÖHM, H.-J., and DEAN, P.M. A validation study on the practical use of automated de novo design. J. Comput.-Aided Mol. Des. 2002, 16, 459-478.
48. BÖHM, H.-J. and SCHNEIDER, G. (Eds). Virtual Screening for Bioactive Molecules. Wiley-VCH, Weinheim, 2000.
49. BAJORATH, J. Integration of virtual and high throughput screening. Nat. Rev. Drug Disc. 2002, 1, 882-894.
50. SMITH, A. Screening for drug discovery: the leading question. Nature 2002, 418, 453-459.
51. OPREA, T.I., DAVIS, A.M., TEAGUE, S.J., and LEESON, P.D. Is there a difference between leads and drugs? A historical perspective. J. Chem. Inf. Comput. Sci. 2001, 41, 1308-1315.
52. TEAGUE, S.J., DAVIS, A.M., LEESON, P.D., and OPREA, T. The design of leadlike combinatorial libraries. Angew. Chem., Int. Ed. 1999, 38, 3743-3748.
53. OPREA, T.I. Current trends in lead discovery: Are we looking for the appropriate properties? J. Comput. Aided. Mol. Des. 2002, 16, 325-334.
54. HANN, M.M., LEACH, A.R., and HARPER, G. Molecular complexity and its impact on the probability of finding leads for drug discovery. J. Chem. Inf. Comput. Sci. 2001, 41, 856-864.
55. MURRAY, C.W. and VERDONK, M.L. The consequences of translational and rotational entropy lost by small molecules on binding to proteins. J. Comput.-Aided Mol. Des. 2002, 16, 741-753.
56. RISHTON, G.M. Nonleadlikeness and leadlikeness in biochemical screening. Drug Disc. Today 2003, 8, 86-96.
57. BLUNDELL, T.L., JHOTI, H., and ABELL, C. High-throughput crystallography for lead discovery in drug design. Nat. Rev. Drug Disc. 2002, 1, 45-54.
58. BOEHM, H.J., BOEHRINGER, M., BUR, D., GMUENDER, H., HUBER, W., KLAUS, W., KOSTREWA, D., KUEHNE, H., LUEBBERS, T., MEUNIER-KELLER, N., and MUELLER, F. Novel inhibitors of DNA gyrase: 3D structure based biased needle screening, hit validation by biophysical methods, 3D guided optimization. A promising alternative to random screening. J. Med. Chem. 2000, 43, 2664-2674.
59. PICKETT, S.D., SHERBORNE, B.S., WILKINSON, T., BENNETT, J., BORKAKOTI, N., BROADHURST, M., HURST, D., KILFORD, I., MCKINNELL, M., and JONES, P.S. Discovery of low molecular weight inhibitors of IMPDH via virtual needle screening. Bioorg. Med. Chem. Lett. 2003, 13, 1691-1694.
60. LIPINSKI, C.A. Drug-like properties and the causes of poor solubility and poor permeability. J. Pharm. Toxicol. Methods 2000, 44, 235-249.
61. GREENE, J., KAHN, S., SAVOJ, H., SPRAGUE, P., and TEIG, S. Chemical function queries for 3D database search. J. Chem. Inf. Comput. Sci. 1994, 34, 1297-1308.
62. SPRAGUE, P.W. Automated chemical hypothesis generation and database searching with CATALYST. Perspect. Drug. Disc. Des. 1995, 3, 1-20.
63. KUBINYI, H. (Ed.). 3D-QSAR in Drug Design. Theory, Methods and Applications. ESCOM, Leiden, Netherlands, 1993.
64. KUBINYI, H., FOLKERS, G., and MARTIN, Y.C. (Eds). 3D-QSAR in Drug Design, Vol. 2. ESCOM, Dordrecht, Netherlands, 1998.
65. HANSCH, C. and LEO, A. (Eds). Exploring QSAR: Fundamentals and Applications in Chemistry and Biology. American Chemical Society, Washington, DC, 1995.
66. DEBNATH, A.K. Quantitative structure-activity relationship (QSAR) paradigm - Hansch era to new millennium. Mini Rev. Med. Chem. 2001, 1, 187-195.
67. KELLOGG, G.E. and SEMUS, S.F. 3D QSAR in modern drug design. In Modern Methods of Drug Discovery, HILLISCH, A. and HILGENFELD, R. (Eds). Birkhäuser, Basel, 2003, 223-241.
68. RCSB Protein Data Bank, from the Research Collaboratory for Structural Bioinformatics, http://www.rcsb.org/pdb/index.html.
69. BERMAN, H.M., WESTBROOK, J., FENG, Z., GILLILAND, G., BHAT, T.N., WEISSIG, H., SHINDYALOV, I.N., and BOURNE, P.E. The protein data bank. Nucleic Acids Res. 2000, 28, 235-242.
70. BOHACEK, R.S., MCMARTIN, C., and GUIDA, W.C. The art and practice of structure-based drug design: a molecular modeling perspective. Med. Res. Rev. 1996, 16, 3-50.
71. KUBINYI, H. Structure-based design of enzyme inhibitors and receptor ligands. Curr. Opin. Drug Disc. Dev. 1998, 1, 4-15.
72. MURCKO, M., CARON, P.R., and CHARIFSON, P.S. Structure-based drug design. Annu. Rep. Med. Chem. 1999, 34, 297-306.
73. KLEBE, G. Recent developments in structure-based drug design. J. Mol. Med. 2000, 78, 269-281.
74. BÖHM, H.-J. and STAHL, M. Structure-based library design: molecular modelling merges with combinatorial chemistry. Curr. Opin. Chem. Biol. 2000, 4, 283-286.
75. MATTOS, C. and RINGE, D. Multiple binding modes. In 3D-QSAR in Drug Design. Theory, Methods and Applications, KUBINYI, H. (Ed.). ESCOM, Leiden, Netherlands, 1993, 226-254.
76. MAIGNAN, S., GUILLOTEAU, J.-P., CHOI-SLEDESKI, Y.M., BECKER, M.R., EWING, W.R., PAULS, H.W., SPADA, A.P., and MIKOL, V. Molecular structures of human factor Xa complexed with ketopiperazine inhibitors: preference for a neutral group in the S1 pocket. J. Med. Chem. 2003, 46, 685-690.
77. TEAGUE, S.J. Implications of protein flexibility for drug discovery. Nat. Rev. Drug Disc. 2003, 2, 527-541.
78. REYDA, S., SOHN, C., KLEBE, G., RALL, K., ULLMANN, D., JAKUBKE, H.D., and STUBBS, M.T. Reconstructing the binding site of factor Xa in trypsin reveals ligand-induced structural plasticity. J. Mol. Biol. 2003, 325, 963-977.
79. LADBURY, J.E. Just add water! The effect of water on the specificity of protein-ligand binding sites and its potential application to drug design. Chem. Biol. 1996, 3, 973-980.
80. STUBBS, M.T., REYDA, S., DULLWEBER, F., MOLLER, M., KLEBE, G., DORSCH, D., MEDERSKI, W.W.K.R., and WURZIGER, H. pH-dependent binding modes observed in trypsin crystals: lessons for structurebased drug design. ChemBioChem 2002, 3, 246-249.
81. DAVIS, A.M., TEAGUE, S.J., and KLEYWEGT, G.J. Application and limitations of X-ray crystallographic data in structure-based ligand and drug design. Angew. Chem., Int. Ed. Engl. 2003, 42, 2718-2736.
82. HOOFT, R.W.W., VRIEND, G., SANDER, C., and ABOLA, E.E. Errors in protein structures. Nature 1996, 381, 272.
83. NISSINK, J.W.M., MURRAY, C., HARTSHORN, M., VERDONK, M.L., COLE, J.C., and TAYLOR, R. A new test set for validating predictions of protein-ligand interaction. Proteins 2002, 49, 457-471.
84. BABINE, R.E. and BENDER, S.L. Molecular recognition of protein-ligand complexes: applications to drug design. Chem. Rev. 1997, 97, 1359-1472.
85. GOHLKE, H. and KLEBE, G. Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors. Angew. Chem., Int. Ed. Engl. 2002, 41, 2644-2676.
86. TAME, J.R.H. Scoring functions: a view from the bench. J. Comput.-Aided Mol. Des. 1999, 13, 99-108.
87. OPRE, T.I. and MARSHALL, G.R. Receptor-based prediction of binding affinities. In 3D-QSAR in Drug Design, Vol. 2, KUBINYI, H., FOLKERS, G., and MARTIN, Y.C. (Eds). Kluwer, Dordrecht, Netherlands, 1998, 35-61.
88. BÖHM, H.J. and STAHL, M. The use of scoring functions in drug discovery applications. In Reviews in Computational Chemistry, Vol. 18, LIPKOWITZ, K.B. and BOYD, D.B. (Eds). Wiley-VCH, Weinheim, 2002, 41-87.
89. GOHLKE, H. and KLEBE, G. Statistical potentials and scoring functions applied to protein-ligand binding. Curr. Opin. Struct. Biol. 2001, 11, 231-235.
90. CHARIFSON, P.S., CORKEREY, J.J., MURCKO, M.A., and WALTERS, W.P. Consensus scoring: a method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins. J. Med. Chem. 1999, 42, 5100-5109.
91. CLARK, R.D., STRIZHEV, A., LEONARD, J.M., BLAKE, J.F., and MATTHEW, J.B. Consensus scoring for ligand/protein interactions. J. Mol. Graph. Mod. 2002, 20, 281-295.
92. GOHLKE, H. and KLEBE, G. DrugScore meets comfa: adaptation of fields for molecular comparison (AFMoC) or how to tailor knowledge-based pair-potentials to a particular protein. J. Med. Chem. 2002, 45, 4153-4170.
93. GOHLKE, H., HENDLICH, M., and KLEBE, G. Knowledge-based scoring function to predict protein-ligand interactions. J. Mol. Biol. 2000, 295, 337-356.
94. CRAMER, R.D., PATTERSON, D.E., and BUNCE, J.E. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc. 1988, 110, 5959-5967.
95. CLARK, M., CRAMER, R.D., JONES, D.M., PATTERSON, D.E., and SIMEROTH, P.E. Comparative molecular field analysis (CoMFA). 2. Towards its use with 3D-structural databases. Tetrahedron. Comput. Methods 1990, 3, 47-59.
96. WOLD, S., ALBANO, C., DUNN, W.J., EDLUND, U., ESBENSON, K., GELADI, P., HELLBERG, S., LINDBERG, W., and SJÖSTRÖM, M. Multivariate data analysis in chemistry. In Chemometrics: Mathematics and Statistics in Chemistry, KOWALSKI, B. (Ed.). Reidel, Dordrecht, Netherlands, 1984, 17-95
97. DUNN, W.J., WOLD, S., EDLUND, U., HELLBERG, S., and GASTEIGER, J. Multivariate structure-activity relationships between data from a battery of biological tests and an ensemble of structural descriptors: the PLS method. Quant. Struct.-Act. Relat. 1984, 3, 131-137.
98. ORTIZ, A.R., PISABARRO, M.T., GAGO, F., and WADE, R.C. Prediction of drug binding affinities by comparative binding energy analysis. J. Med. Chem. 1995, 38, 2681-2691.
99. ORTIZ, A.R., PASTOR, M., PALOMER, A., CRUCIANI, G., GAGO, F., and WADE, R.C. Reliability of comparative molecular field analysis models: effects of data scaling and variable selection using a set of human synovial fluid phospholipase A2 inhibitors. J. Med. Chem. 1997, 40, 1136-1148.
100. PEREZ, C., PASTOR, M., ORTIZ, A.R., and GAGO, F. Comparative binding energy analysis of HIV-1 protease inhibitors: incorporation of solvent effects and validation as a powerful tool in receptor-based drug design. J. Med. Chem. 1998, 41, 836-852.
101. WANG, T. and WADE, R.C. Comparative binding energy (COMBINE) analysis of influenza neuraminidase-inhibitor complexes. J. Med. Chem. 2001, 44, 961-971.
102. ROGNAN, D., LAUEMOLLER, S.L., HOLM, A., BUUS, S., and TSCHINKE, V. Predicting binding affinities of protein ligands from three-dimensional models: application to peptide binding to class i major histocompatibility proteins. J. Med. Chem. 1999, 42, 4650-4658.
103. MURRAY, C.W., AUTON, T.R., and ELDRIDGE, M.D. Empirical scoring functions. II. The testing of an empirical scoring function for the prediction of ligand-receptor affinities and the use of Bayesian regression to improve the quality of the model. J. Comput.-Aided Mol. Des. 1998, 12, 503-519.
104. ELDRIDGE, M.D., MURRAY, C.W., AUTON, T.R., PAOLINI, G.V., and MEE, R.P. Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. J. Comput.-Aided Mol. Des. 1997, 11, 425-445.
105. KLEBE, G., ABRAHAM, U., and MIETZNER, T. Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. J. Med. Chem. 1994, 37, 4130-4146.
106. WOLD, S. Cross-validatory estimation of the number of component in factor and principal component models. Technometrics 1978, 4, 397-405
107. CRAMER, R.D., BUNCE, J.D. and PATTERSON, D.E. Crossvalidation, bootstrapping and partial least squares compared with multiple regression in conventional QSAR studies. Quant. Struct.-Act. Relat. 1988, 7, 18-25.
108. WALLER, C.L., OPREA, T.I., GIOLITTI, A., and MARSHALL, G.R. Three-dimensional QSAR of human immunodeficiency virus (I) protease inhibitors. 1. A CoMFA study employing experimentally-determined alignment rules. J. Med. Chem. 1993, 36, 4152-4160.
109. OPREA, T.I., WALLER, C.L., and MARSHALL, G.R. Three-dimensional quantitative structure-activity relationship of human immunodeficiency virus (I) protease inhibitors. 2. Predictive power using limited exploration of alternate binding modes. J. Med. Chem. 1994, 37, 2206-2215.
110. WEI, D.T., MEADOWS, J.C., and KELLOGG, G.E. Effects of entropy on QSAR equations for HIV-1 protease: 1. Using hydropathic binding descriptors. 2. Unrestrained complex structure optimizations. Med. Chem. Res. 1997, 7, 259-270.
111. SIPPL, W. Receptor-based 3D QSAR analysis of estrogen receptor ligands - merging the accuracy of receptor-based alignments with the computational efficiency of ligand-based methods. J. Comput.-Aided Mol. Des. 2000, 14, 559-572.
112. SIPPL, W., CONTRERAS, J.M., PARROT, I., RIVAL, Y.M., and WERMUTH, C.G. Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors. J. Comput.-Aided Mol. Des. 2001, 15, 395-410.
113. MATTER, H., SCHWAB, W., BARBIER, D., BILLEN, G., HAASE, B., NEISES, B., SCHUDOK, M., THORWART, W., BRACHVOGEL, V., LÖNZE, P., and WEITHMANN, K.U. Quantitative structure-activity relationship of human neutrophil collagenase (MMP-8) inhibitors using comparative molecular field and X-Ray structure analysis. J. Med. Chem. 1999, 42, 1908-1920.
114. MATTER, H. and SCHWAB, W. Affinity and selectivity of matrix metalloproteinase inhibitors: a chemometrical study from the perspective of ligands and proteins. J. Med. Chem. 1999, 42, 4506-4523.
115. NAUMANN, T. and MATTER, H. Structural classification of protein kinases using 3D molecular interaction field analysis of their ligand binding sites: target family landscapes. J. Med. Chem. 2002, 45, 2366-2378.
116. MATTER, H., DEFOSSA, E., HEINELT, U., BLOHM, P.M., SCHNEIDER, D., MÜLLER, A., HEROK, S., SCHREUDER, H., LIESUM, A., BRACHVOGEL, V., LÖNZE, P., WALSER, A., AL-OBEIDI, F., and WILDGOOSE, P. Design and quantitative structure-activity relationship of 3-amidinobenzyl-1H-indole-2-carboxamides as potent, non-chiral and selective inhibitors of blood coagulation factor Xa. J. Med. Chem. 2002, 45, 2749-2769.
117. MATTER, H. Computational approaches towards the quantification of molecular diversity and design of compound libraries. In Modern Methods of Drug Discovery, HILLISCH, A. and HILGENFELD, R. (Eds). Birkhäuser, Basel, 2003, 125-156.
118. SCHUFFENHAUER, A., ZIMMERMANN, J., STOOP, R., VAN DER VYVER, J.J., LECCHINI, S., and JACOBY, E. An ontology for pharmaceutical ligands and its application for in silico screening and library design. J. Chem. Inf. Comput. Sci. 2002, 42, 947-955.
119. SCHUFFENHAUER, A., FLOERSHEIM, P., ACKLIN, P., and JACOBY, E. Similarity metrics for ligands reflecting the similarity of the target proteins. J. Chem. Inf. Comput. Sci. 2003, 43, 391-405.
120. WONG, G., KOEHLER, K.F., SKOLNICK, P., GU, Z.-Q., ANANTHAN, S., SCHÖNHOLZER, P., HUNKELER, W., ZHANG, W., and COOK, J.M. Synthetic and computerassisted analysis of the structural requirements for selective, high-affinity ligand binding to diazepam-insensitive benzodiazepine receptors. J. Med. Chem. 1993, 36, 1820-1830.
121. MATTER, H., DEFOSSA, E., HEINELT, U., NAUMANN, T., SCHREUDER, H. and WILDGOOSE, P. Combining structure-based design and 3D-QSAR towards the discovery of non-chiral, potent and selective factor Xa inhibitors. In Rational Approaches to Drug Design, Proceedings of the 13th European Symposium on Quantitative Structure-Activity Relationships, HÖLTJE, H.-D. and SIPPL, W. (Eds). Prous Science, Barcelona, 2001, 177-185.
122. KASTENHOLZ, M.A., PASTOR, M., CRUCIANI, G., HAAKSMA, E.E.J., and FOX, T. GRID/CPCA: A new computational tool to design selective ligands. J. Med. Chem. 2000, 43, 3033-3044.
123. BOEHM, M., STUERZEBECHER, J., and KLEBE, G. Three-dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factor Xa. J. Med. Chem. 1999, 42, 458-477.
124. CHEN, Q., WU, C., MAXWELL, D., KRUDY, G.A., DIXON, R.A.F., and YOU, T.J. A 3D QSAR analysis of in vitro binding affinity and selectivity of 3-isoxazolylsulfonylaminothiophenes as endothelin receptor antagonists. Quant. Struct.-Act. Relat. 1999, 18, 124-133.
125. BOSTROM, J., BOEHM, M., GUNDERTOFTE, K., and KLEBE, G. A 3D QSAR study on a set of dopamine D4 receptor antagonists. J. Chem. Inf. Comput. Sci. 2003, 43, 1020-1027.
126. BALLE, T., ANDERSEN, K., SOBY, K.K., and LILJEFORS, T. α 1 Adrenoceptor subtype selectivity 3D-QSAR models for a new class of α-1 adrenoceptor antagonists derived from the novel antipsychotic sertindole. J. Mol. Graph. Mod. 2003, 21, 523-534.
127. GOODFORD, P. A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. J. Med. Chem. 1985, 28, 849-857.
128. NISSINK, J.W.M., VERDONK, M.L., and KLEBE, G. Simple knowledge-based descriptors to predict protein-ligand interactions. Methodology and validation. J. Comput.-Aided Mol. Des. 2000, 14, 787-803.
129. VERDONK, M.L., COLE, J.C., WATSON, P., GILLET, V., and WILLETT, P. SuperStar: improved knowledge-based interaction fields for protein binding sites. J. Mol. Biol. 2001, 307, 841-859.
130. GOHLKE, H., HENDLICH, M., and KLEBE, G. Predicting binding modes, binding affinities and ''hot spots'' for protein-ligand complexes using a knowledge-based scoring function. Perspect. Drug Disc. Dev. 2000, 20, 115-144.
131. WESTERHUIS, J.A., KOURTI, T., and MACGREGOR, J.F. Analysis ofmultiblock and hierarchical PCA and PLS models. J. Chemometrics 1998, 12, 301-321.
132. RIDDERSTRÖM, M., ZAMORA, I., FJELLSTRÖM, O., and ANDERSSON, T.B. Analysis of selective regions in the active sites of human cytochromes P450, 2C8, 2C9, 2C18, and 2C19 homology models using GRID/CPCA. J. Med. Chem. 2001, 44, 4072-4081.
133. WILLIAMS, P.A., COSME, J., SRIDHAR, V., JOHNSON, E.F., and MCREE, D.E. Mammalian microsomal cytochrome P450 monooxygenase: structural adaptations for membrane binding and functional diversity. Mol. Cell 2000, 5, 121-131.
134. TERP, G.E., CRUCIANI, G., CHRISTENSEN, I.T., and JORGENSEN, F.S. Structural differences of matrix metalloproteinases with potential implications for inhibitor selectivity examined by the GRID/CPCA approach. J. Med. Chem. 2002, 45, 2675-2684.
135. MYSHKIN, E. and WANG, B. Chemometrical classification of ephrin ligands and eph kinases using GRID/CPCA approach. J. Chem. Inf. Comput. Sci. 2003, 43, 1004-1010.
136. KURZ, M., BRACHVOGEL, V., MATTER, H., STENGELIN, S., THÜRING, H., and KRAMER, W. Insights Into the Bile Acid Transportation System the human ileal lipid-binding protein (ILBP) - cholyltaurine complex and its comparison to homologous structures. Proteins 2003, 50, 312-328.
137. SHERIDAN, R.P., HOLLOWAY, M.K., MCGAUGHEY, G., MOSLEY, R.T., and SINGH, S.B. A simplemethod for visualizing the differences between related receptor sites. J. Mol. Graph. Mod. 2002, 21, 71-79.
138. MATTER, H., NAUMANN, T., and PIRARD, B. Target family landscapes to match ligand selectivity with binding site topology in chemical biology. In EuroQSAR2002: Designing Drugs and Crop Protectants: Processes, Problems and Solutions, FORD, M., LIVINGSTONE, D., DEARDEN, J., and VAN DE WATERBEEMD, H. (Eds). Blackwell, Oxford, UK, 2003, 183-185.
139. LAPINSH, M., PRUSIS, P., GUTCAITS, A., LUNDSTEDT, T., and WIKBERG, J.E.S. Development of proteo-chemometrics: a novel technology for the analysis of drug-receptor interactions. Biochim. Biophys. Acta 2001, 1525, 180-190.
140. LAPINSH, M., PRUSIS, P., MUTULE, I., MUTULIS, F., and WIKBERG, J.E.S. QSAR and proteo-chemometric analysis of the interaction of a series of organic compounds with melanocortin receptor subtypes. J. Med. Chem. 2003, 46, 2572-2579.
141. LAPINSH, M., PRUSIS, P., LUNDSTEDT, T., and WIKBERG, J.E.S. Proteochemometrics modeling of the interaction of amine G-protein coupled receptors with a diverse set of ligands. Mol. Pharm. 2002, 61, 1465-1475.
142. EKINS, S., WALLER, C.L., SWANN, P.W., CRUCIANI, G., WRIGHTON, S.A., and WIKEL, J.H. Progress in predicting human ADME parameters in silico. J. Pharm. Toxicol. Methods 2000, 44, 251-272.
143. LIPINSKI, C.A., LOMBARDO, F., DOMINY, B.W., and FEENEY, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 2001, 46, 3-26.
144. JORGENSEN, W.L. and DUFFY, E.M. Prediction of drug solubility from structure. Adv. Drug Deliv. Rev 2002, 54, 355-366.
145. ROSENBERG, M.F., KAMIS, A.B., CALLAGHAN, R., HIGGINS, C.F., and FORD, R.C. Three-dimensional structures of the mammalian multidrug resistance P-glycoprotein demonstrate major conformational changes in the transmembrane domains upon nucleotide binding. J. Biol. Chem. 2003, 278, 8294-8299.
146. LITMAN, T., DRULEY, T.E., STEIN, W.D., and BATES, S.E. From MDR to MXR: new understanding of multidrug resistance systems, their properties and clinical significance. Cell. Mol. Life Sci. 2001, 58, 931-959.
147. ZHAO, Y.H., LE, J., ABRAHAM, M.H., HERSEY, A., EDDERSHAW, P.J., LUSCOMBE, C.N., BUTINA, D., BECK, G., SHERBORNE, B., COOPER, I., and PLATTS, J.A. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. J. Pharm. Sci. 2001, 90, 749-784.
148. FU, X.C., LIANG, W.Q., and YU, Q.S. Correlation of drug absorption with molecular charge distribution. Pharmazie 2001, 56, 267-268.
149. AGATONOVICH-KUSTRIN, S., BERESFORD, R., and YUSOF, A.P.M. ANN modeling of the penetration across a polydimethylsiloxane membrane from theoretically derived molecular descriptors. J. Pharm. Biomed. Anal. 2001, 25, 227-237.
150. NORINDER, U. andÖSTERBERG, T. Theoretical calculation and prediction of drug transport processes using simple parameters and partial least squares projections to latent structures (PLS) statistics. The use of electrotopological state indices. J. Pharm. Sci. 2001, 90, 1076-1085.
151. AGORAM, B., WOLTOSZ, W.S., and BOLGER, M.B. Predicting the impact of physiological and biochemical processes on oral drug bioavailability. Adv. Drug Deliv. Rev. 2001, 90, S41-S67.
152. NORRIS, D.A., LEESMAN, G.D., SINKO, P.J., and GRASS, G.M. Development of predictive pharmacokinetic simulation models for drug discovery. J. Control Relat. 2000, 65, 55-62.
153. PARROTT, N. and LAVÉ, T. Prediction of intestinal absorption: comparative assessment of Gastroplus and Idea. Eur. J. Pharm. Sci. 2002, 17, 51-61.
154. KARIV, I., ROURICK, R.A., KASSEL, D.B., and CHUNG, T.D.Y. Improvement of ''hit-to-lead'' optimization by integration of in vitro HTS experimental models for early determination of pharmacokinetic properties. Comb. Chem. High Throughput Screen. 2002, 5, 459-472.
155. BERESFORD, A.P., SELICK, H.E., and TARBIT, M.H. The emerging importance of predictive ADME simulation in drug discovery. Drug Disc. Today 2002, 7, 109-116.
156. YOSHIDA, F. and TOPLISS, J.G. QSAR model for drug human oral bioavailability. J. Med. Chem. 2000, 43, 2575-2585.
157. MADAN, A., USUKI, E., BURTON, L.A., OGILVIE, B.W., and PARKINSON, A. In vitro approaches for studying the inhibition of drug-metabolizing enzymes and identifying the drug-metabolizing enzymes responsible for the metabolism of drugs. In Drug Drug Interaction, RODRIGUEZ, A.D. (Ed.). Marcel Dekker, New York, 2002, 217-294.
158. DE GROOT, M.J., ALEX, A.A., and JONES, B.C. Development of a combined protein and pharmacophore model for cytochrome P450 2C9. J. Med. Chem. 2002, 45, 1983-1993.
159. BIDWELL, L.M., MCMANUS, M., GAEDIGK, A., KAKUTA, Y., NEGISHI, M., PEDERSEN, L., and MARTIN, J.L. Crystal structure of human catecholamine sulfotransferase. J. Mol. Biol. 1999, 293, 521-530.
160. EKINS, S., DE GROOT, M., and JONES, J.P. Pharmacophore and three-dimensional quantitative structure activity relationship methods for modeling cytochrome P450 active sites. Drug Metab. Dispos. 2001, 29, 936-944.
161. HIGGINS, L., KORZEKWA, K.R., RAO, S., SHOU, M., and JONES, J.P. An assessment of the reaction energetics for cytochrome P450-mediated reactions. Arch. Biochem. Biophys. 2001, 385, 220-230.
162. SINGH, S.B., SHEN, L.Q., WALKER, M.J., and SHERIDAN, R.P. Amodel for predicting likely sites of CYP3A4-mediated metabolism on drug-like molecules. J. Med. Chem. 2003, 46, 1330-1336.
163. SHEN, M., XIAO, Y., GOLBRAIKH, A., GOMBAR, V.K., and TROPSHA, A. Development and validation of k-nearest-neighbor QSPR models of metabolic stability of drug candidates. J. Med. Chem. 2003, 46, 3013-3020.
164. LANGOWSKI, J. and LONG, A. Computer systems for the prediction of xenobiotic metabolism. Adv. Drug Deliv. Rev. 2002, 54, 407-415.
165. GREENE, N. Computer systems for the prediction of toxicity: an update. Adv. Drug Deliv. Rev. 2002, 54, 417-431.
166. VANDENBERG, J.I., WALKER, B.D., and CAMPBELL, T.J. HERG K+ channels: friend and foe. Trends Pharmacol. Sci. 2001, 22, 240-246.
167. VAN DE WATERBEEMD, H., SMITH, D.A., BEAUMONT, K., and WALKER, D.K. Property-based design: optimization of drug absorption and pharmacokinetics. J. Med. Chem. 2001, 44, 1313-1333.
168. VAN DE WATERBEEMD, H. and GIFFORD, E. ADMET in silico modelling: towards prediction paradise? Nat. Drug Disc. 2003, 2, 192-204.
169. CRUCIANI, G., CRIVORI, P., CARRUPT, P.A., and TESTA, B. Molecular fields in quantitative structure-permeation relationships: the VolSurf approach. THEOCHEM 2000, 503, 17-30.
170. CRUCIANI, G., PASTOR, M., and GUBA, W. VolSurf: a new tool for the pharmacokinetic optimization of lead compounds. Eur. J. Pharm. Sci. 2000, 11, S29-S39.
171. GUBA, W. and CRUCIANI, G. Molecular field-derived descriptors for the multivariate modelling of pharmacokinetic data. In Molecular Modelling and Prediction of Bioactivity, Proceedings of the 12th European Symposium on Quantitative Structure-Activity Relationships (QSAR'98), GUNDERTOFTE, K. and JORGENSEN, F.S. (Eds). Plenum Press, New York, 2000, 89-95.
172. ALIFRANGIS, L.H., CHRISTENSEN, I.T., BERGLUND, A., SANDBERG, M., HOVGAARD, L., and FROKJAER, S. Structure-property model for membrane partitioning of oligopeptides. J. Med. Chem. 2000, 43, 103-113.
173. CRIVORI, P., CRUCIANI, G., CARRUPT, P.A., and TESTA, B. Predicting blood-brain barrier permeation from three-dimensional molecular structure. J. Med. Chem. 2000, 43, 2204-2216.
174. PFEIFFER-MAREK, S., MATTER, H., ENGLERT, H., GERLACH, U., KNIEPS, S., SCHUDOK, M., and LEHR, K.H. Using VolSurf descriptors to model pharmacokinetic properties during lead optimization. In Designing Drugs and Crop Protectants, Proceedings of the 14th European Symposium on Quantitative Structure-Activity Relationship (QSAR 2002), FORD, M., LIVINGSTONE, D., DEARDEN, J., and VAN DE WATERBEEMD, H. (Eds). Blackwell Publishers, Oxford, 2003, 104-105.
175. COLMENAREJO, G., ALVAREZ-PEDRAGLIO, A., and LAVANDERA, J.-L. Cheminformatic models to predict binding affinities to human serum albumin. J. Med. Chem. 2001, 44, 4370-4378.
176. PETITPAS, I., BHATTACHARYA, A.A., TWINE, S., EAST, M., and CURRY, S. Crystal structure analysis of warfarin binding to human serum albumin. Anatomy of drug site I. J. Biol. Chem. 2001, 276, 22804-22809.
177. ZHU, C., JIANG, L., CHEN, T.M., and HWANG, K.K. A comparative study of artificial membrane permeability assay for high throughput profiling of drug absorption potential. Eur. J. Med. Chem. 2002, 37, 399-407.
178. SALMINEN, T., PULLI, A., and TASKINEN, J. Relationship between immobilised artificial membrane chromatographic retention and the brain penetration of structurally diverse drugs. J. Pharm. Biomed. Anal. 1997, 15, 469-477.
179. IRVINE, J.D., LOCKHART, L.T., CHEONG, J., TOLAN, J.W., SELICK, H.E., and GROVE, J.R. MDCK (Madin-Darby canine kidney) cells: A tool for membrane permeability screening. J. Pharm. Sci. 1999, 88, 28-33.
180. YAZDANIAN, M., GLYNN, S.L., WRIGHT, J.L., and HAWI, A. Correlating partitioning and Caco-2 cell permeability of structurally diverse small molecular weight compounds. Pharm. Res. 1998, 15, 1490-1494.
181. DOYLE, D.A., MORAIS CABRAL, J., PFUETZNER, R.A., KUO, A., GULBIS, J.M., COHEN, S.L., CHAIT, B.T., and MACKINNON, R. The structure of the potassium channel: molecular basis of K+ conduction and selectivity. Science 1998, 280, 69-77.
182. MITCHESON, J.S., CHEN, J., LIN, M., CULBERSON, C., and SANGUINETTI, M.C. A structural basis for drug-induced long QT syndrome. Proc. Nat. Acad Sci.USA 2000, 97, 12329-12333.
183. PEARLSTEIN, R., VAZ, R., and RAMPE, D. Understanding the structure-activity relationship of the human ether-a-go-go-related gene cardiac K+ channel. A model for bad behavior. J. Med. Chem. 2003, 46, 2017-2022.
184. ROCHE, O., TRUBE, G., ZUEGGE, J., PFLIMLIN, P., ALANINE, A., and SCHNEIDER, G. A virtual screening method for prediction of the hERG potassium channel liability of compound libraries. ChemBioChem 2002, 3, 455-459.
185. CAVALLI, A., POLUZZI, E., DE PONTI, F., and RECANATINI, M. Toward a pharmacophore for drugs inducing the long QT syndrome: insights from a CoMFA study of HERG K+ channel blockers. J. Med. Chem. 2002, 45, 3844-3853.
186. MATTER, H. unpublished results.
187. PEARLSTEIN, R.A., VAZ, R.J., KANG, J., CHEN, X.-L., PREOBRAZHENSKAYA, M., SHCHEKOTIKHIN, A.E., KOROLEV, A.M., LYSENKOVA, L.N., MIROSHNIKOVA, O.V., HENDRIX, J., and RAMPE, D. Characterization of HERG potassium channel inhibition using CoMSiA 3D QSAR and homology modeling approaches. Bioorg. Med. Chem. Lett. 2003, 13, 1829-1835.
188. JIANG, Y., LEE, A., CHEN, J., CADENE, M., CHAIT, B.T., and MACKINNON, R. Crystal structure and mechanism of a calcium-gated potassium channel. Nature 2002, 417, 515-522.
189. FRIESEN, R.W., DUCHARME, Y., BALL, R.G., BLOUIN, M., BOULET, L., COTE, B., FRENETTE, R., GIRARD, M., GUAY, D., HUANG, Z., JONES, T.R., LALIBERTE, F., LYNCH, J.J., MANCINI, J., MARTINS, E., MASSON, P., MUISE, E., PON, D.J., SIEGL, P.K.S., STYHLER, A., TSOU, N.N., TURNER, M.J., YOUNG, R.N., and GIRARD, Y. Optimization of a tertiary alcohol series of phosphodiesterase-4 (PDE4) inhibitors: structure-activity relationship related to PDE4 inhibition and human ether-a-go-go related gene potassium channel binding affinity. J. Med. Chem. 2003, 46, 2413-2426.
190. STRESSER, D.M., BLANCHARD, A.P., TURNER, S.D., ERVE, J.C.L., DANDENEAU, A.A., MILLER, V.P., and CRESPI, C.L. Substrate-dependent modulation of CYP3A4 catalytic activity: analysis of 27 test compounds with four fluorometric substrates. Drug Metab. Dispos. 2000, 28, 1440-1448.
191. LEWIS, D.F.V. Structural characteristics of human P450s involved in drug metabolism: QSARs and lipophilicity profiles. Toxicology 2000, 144, 197-203.
192. LEWIS, D.F.V. Essential requirements for substrate binding affinity and selectivity toward human CYP2 family enzymes. Arch. Biochem. Biophys. 2003, 409, 32-44.
193. EKINS, S., BRAVI, G., RING, B.J., GILLESPIE, T.A., GILLESPIE, J.S., VAMDENBRANDEN, M., WRIGHTON, S.A., and WIKEL, J.H. Three-dimensional quantitative structure activity relationship analyses of substrates for CYP2B6. J. Pharm. Exp. Ther. 1999, 288, 21-29.
194. EKINS, S., BRAVI, G., WIKEL, J., and WRIGHTON, S.A. Three-dimensional quantitative structure activity relationship analysis of cytochrome P-450 3A4 substrates. J. Pharm. Exp. Ther. 1999, 291, 424-433.
195. EKINS, S., BRAVI, G., BINKLEY, S., GILLESPIE, J.S., RING, B.J., WIKEL, J.H., and WRIGHTON, S.A. Three- and four-dimensional quantitative structure activity relationship analyses of cytochrome P-450 3A4 inhibitors. J. Pharm. Exp. Ther. 1999, 290, 429-438.
196. EKINS, S., BRAVI, G., BINKLEY, S., GILLESPIE, J.S., RING, B.J., WIKEL, J.H., and WRIGHTON, S.A. Three- and four-dimensional-quantitative structure activity relationship (3D/4D-QSAR) analyses of CYP2C9 inhibitors. Drug Metab. Dispos. 2000, 28, 994-1002.
197. EKINS, S., BRAVI, G., BINKLEY, S., GILLESPIE, J.S., RING, B.J., WIKEL, J.H., and WRIGHTON, S.A. Three and four dimensional-quantitative structure activity relationship (3D/4D-QSAR) analyses of CYP2D6 inhibitors. Pharmacogenetics 1999, 9, 477-489.
198. RAO, S., AOYAMA, R., SCHRAG, M., TRAGER, W.F., RETTIE, A., and JONES, J.F. A Refined 3-dimensional QSAR of cytochrome P450 2C9: computational predictions of drug interactions. J. Med. Chem. 2000, 43, 2789-2796.
199. AFZELIUS, L., MASIMIREMBWA, C.M., KARLEN, A., ANDERSSON, T.B., and ZAMORA, I. Discriminant and quantitative PLS analysis of competitive CYP2C9 inhibitors versus non-inhibitors using alignment independent GRIND descriptors. J. Comput.-Aided Mol. Des. 2002, 16, 443-458.
200. PASTOR, M., CRUCIANI, G., MCLAY, I., PICKETT, S., and CLEMENTI, S. GRid-INdependent Descriptors (GRIND): a novel class of alignment-independent threedimensional molecular descriptors. J. Med. Chem. 2000, 43, 3233-3243.
201. DE GROOT, M.J., ACKLAND, M.J., HORNE, V.A., ALEX, A.A., and JONES, B.C. Novel approach to predicting P450-mediated drug metabolism: development of a combined protein and pharmacophore model for CYP2D6. J. Med. Chem. 1999, 42, 1515-1524.
202. DE GROOT, M.J., ACKLAND, M.J., HORNE, V.A., ALEX, A.A., and JONES, B.C. A novel approach to predicting P450 mediated drug metabolism. CYP2D6 catalyzed N-dealkylation reactions and qualitative metabolite predictions using a combined protein and pharmacophore model for CYP2D6. J. Med. Chem. 1999, 42, 4062-4070.
203. ZAMORA, I., AFZELIUS, L., and CRUCIANI, G. Predicting drug metabolism: a site of metabolism prediction tool applied to the cytochrome P450 2C9. J. Med. Chem. 2003, 46, 2313-2324.
204. WESTER, M.R., JOHNSON, E.F., MARQUES-SOARES, C., DIJOLS, S., DANSETTE, P.M., MANSUY, D., and STOUT, C.D. Structure of mammalian cytochrome P450 2C5 complexed with diclofenac at 2.1 A resolution: evidence for an induced fit model of substrate binding. Biochem. 2003, 42, 9335-9345.
205. WESTER, M.R., JOHNSON, E.F., MARQUES-SOARES, C., DANSETTE, P.M., MANSUY, D., and STOUT, C.D. Structure of a substrate complex of mammalian cytochrome P450 2C5 at 2.3 a resolution: evidence for multiple substrate binding modes. Biochem. 2003, 42, 6370-6379.
206. WILLIAMS, P.A., COSME, J., WARD, A., ANGOVE, H.C., VINKOVIC, D.M., and JHOTI, H. Crystal structure of human cytochrome P450 2C9 with bound warfarin. Nature 2003, 424, 464-468.
207. HELLBERG, S., ERIKSSON, L., JONSSON, J., LINDGREN, F., SJÖSTRÖM, M., SKAGERBERG, B., WOLD, S., and ANDREWS, P. Minimum analog peptide sets (MAPS) for quantitative structureactivity relationships. Int. J. Pept. Prot. Res. 1991, 37, 414-424.
208. ATTERWILL, C.K. and WING, M.G. In vitro preclinical lead optimization technologies (PLOTs) in pharmaceutical development. Toxicol. Lett. 2002, 127, 143-151.
209. LINUSSON, A., GOTTFRIES, J., OLSSON, T., OERNSKOV, E., FOLESTAD, S., NORDEN, B., and WOLD, S. Statistical molecular design, parallel synthesis, and biological evaluation of a library of thrombin inhibitors. J. Med. Chem. 2001, 44, 3424-3439.
210. ERIKSSON, U.G., BREDBERG, U., GISLEN, K., JOHANSSON, L.C., FRISON, L., AHNOFF, M., and GUSTAFSSON, D. Pharmacokinetics and pharmacodynamics of ximelagatran, a novel oral direct thrombin inhibitor, in young healthy male subjects. Eur. J. Clin. Pharmacol. 2003, 59, 35-43.
211. SUGANO, K., YOSHIDA, S., TAKAKU, M., HARAMURA, M., SAITOH, R., NABUCHI, Y., and USHIO, H. Quantitative structure-intestinal permeability relationship of benzamidine analogue thrombin inhibitor. Bioorg. Med. Chem. Lett. 2000, 10, 1939-1942.
212. BURGEY, C.S., ROBINSON, K.A., LYLE, T.A., SANDERSON, P.E.J., LEWIS, S.D., LUCAS, B.J., KRUEGER, J.A., SINGH, R., MILLER-STEIN, C., WHITE, R.B., WONG, B., LYLE, E.A., WILLIAMS, P.D., COBURN, C.A., DORSEY, B.D., BARROW, J.C., STRANIERI, M.T., HOLAHAN, M.A., SITKO, G.R., COOK, J.J., MCMASTERS, D.R., MCDONOUGH, C.M., SANDERS, W.M., WALLACE, A.A., CLAYTON, F.C., BOHN, D., LEONARD, Y.M., DETWILER, T.J., LYNCH, J.J., YAN, Y., CHEN, Z., KUO, L., GARDELL, S.J., SHAFER, J.A., and VACCA, J.P. Metabolism-directed optimization of 3-aminopyrazinone acetamide thrombin inhibitors. Development of an orally bioavailable series containing P1 and P3 pyridines. J. Med. Chem. 2003, 46, 461-473.
213. HASEGAWA, K., SHINDOH, H., SHIRATORI, Y., OHTSUKA, T., AOKI, Y., ICHIHARA, S., HORII, I., and SHIMMA, N. Cassette dosing approach and quantitative structure-pharmacokinetic relationship study of antifungal N-myristoyltransferase inhibitors. J. Chem. Inf. Comput. Sci. 2002, 42, 968-975.
214. MCKENNA, J.M., HALLEY, F., SOUNESS, J.E., MCLAY, I.M., PICKETT, S.D., COLLIS, A.J., PAGE, K., and AHMED, I. An algorithm-directed two component library synthesized via solid-phase methodology yielding potent and orally bioavailable p38 MAP kinase inhibitors. J. Med. Chem. 2002, 45, 2173-2184.
215. PICKETT, S.D., MCLAY, I.M., and CLARK, D.E. Enhancing the hit-to-lead properties of lead optimization libraries. J. Chem. Inf. Comput. Sci. 2000, 40, 263-272.
216. CHOI-SLEDESKI, Y.M., KEARNEY, R., POLI, G., PAULS, H., GARDNER, C., GONG, Y., BECKER, M., DAVIS, R., SPADA, A., LIANG, G., CHU, V., BROWN, K., COLLUSSI, D., LEADLEY, R., REBELLO, S., MOXEY, P., MORGAN, S., BENTLEY, R., KASIEWSKI, C., MAIGNAN, S., GUILLOTEAU, J.P., and MIKOL, V. Discovery of an orally efficacious inhibitor of coagulation factor Xa which incorporates a neutral P1 ligand. J. Med. Chem. 2003, 46, 681-684.
217. TUCKER, T.J., BRADY, S.F., LUMMA, W.C., LEWIS, S.D., GARDELL, S.J., NAYLOR-OLSEN, A.M., YAN, Y., SISKO, J.T., STAUFFER, K.J., LUCAS, B.J., LYNCH, J.J., COOK, J.J., STRANIERI, M.T., HOLAHAN, M.A., LYLE, E.A., BASKIN, E.P., CHEN, I.W., DANCHECK, K.B., KRUEGER, J.A., COOPER, C.M., and VACCA, J.P. Design and synthesis of a series of potent and orally bioavailable noncovalent thrombin inhibitors that utilize nonbasic groups in the P1 position. J. Med. Chem. 1998, 41, 310-319.
218. MATTER, H., SCHUDOK, M., SCHWAB, W., THORWART, W., BARBIER, D., BILLEN, G., HAASE B., NEISES, B., WEITHMANN, K.U., and WOLLMANN, T. Tetrahydroisoquinoline-3-carboxylate based matrix metalloproteinase inhibitors: design, synthesis and structure-activity relationship. Bioorg. Med. Chem. 2002, 10, 3529-3544.
219. BARINGHAUS, K.H., MATTER, H., STENGELIN, S., and KRAMER, W. Substrate specificity of the ileal and the hepatic Na+/bile acid cotransporters of the rabbit. II. A reliable 3D QSAR pharmacophore model for the ileal Na+/bile acid cotransporter. J. Lipid Res. 1999, 40, 2158-2168.