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Approaches to Target Class Combinatorial Library Design

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Chemoinformatics

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 275))

Abstract

The wealth of information available from the solution of the human genome has dramatically altered the nature of combinatorial library design. While single-target-focused library design remains an important objective, creation of libraries directed toward families of receptors such as GPCRs, kinases, nuclear hormone receptors, and proteases, has replaced the generation of libraries based primarily on diversity. Although diversity-based design still plays a role for receptors with no known ligands, more knowledge-based approaches are required for target class design. This chapter discusses some of the possible design methods and presents examples where they are available.

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References

  1. Bures, M. G. and Martin, Y. C. (1998) Computational methods in molecular diversity and combinatorial chemistry. Curr. Opin. Chem. Biol. 2, 376–380.

    Article  PubMed  CAS  Google Scholar 

  2. Van Drie, J. H. and Lajiness, M. S. (1998) Approaches to virtual library design. Drug Discovery Today 3, 274–283.

    Article  Google Scholar 

  3. Spellmeyer, D. C. and Grootenhuis, P. D. J. (1999) Recent developments in molecular diversity: Computational approaches to combinatorial chemistry. Annu. Rep. Med. Chem. 34, 287–296.

    Article  CAS  Google Scholar 

  4. Drewry, D. H. and Young, S. S. (1999) Approaches to the design of combinatorial libraries. Chemom. Intell. Lab. Syst. 48, 1–20.

    Article  CAS  Google Scholar 

  5. Agrafiotis, D. K., Myslik, J. C., and Salemme, F. R. (1999) Advances in diversity profiling and combinatorial series design. Annu. Rep. Comp. Chem. Mol. Diversity 2, 71–92.

    CAS  Google Scholar 

  6. Leach, A. R. and Hann, M. M. (2000) The in silico world of virtual libraries. Drug Discovery Today 5, 326–336.

    Article  PubMed  CAS  Google Scholar 

  7. Lewis, R. A., Pickett, S. D., and Clark, D. E. (2000) Computer-aided molecular diversity analysis and combinatorial library design. In Reviews in Computational Chemistry, Lipkowitz, K. B. and Boyd, D. B. (eds.), Wiley-VCH, New York, Vol. 16, pp. 1–51.

    Chapter  Google Scholar 

  8. Willett, P. (2000) Chemoinformatics—similarity and diversity in chemical libraries. Curr. Opin. Biotechnol. 11, 85–88.

    Article  PubMed  CAS  Google Scholar 

  9. Lipinski, C. A., Lombardo F., Dominy, B. W., and Feeney, P. J. (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 23, 3–25.

    Article  CAS  Google Scholar 

  10. Palm, K., Stenberg, P., Luthman, K., and Artursson, P. (1997) Polar molecular surface properties predict the intestinal absorption of drugs in humans. Pharm. Res. 14, 568–571.

    Article  PubMed  CAS  Google Scholar 

  11. van de Waterbeemd, H., Smith, D. A., Beaumont, K., and Walker, D. K. (2001) Property-based design: optimization of drug absorption and pharmacokinetics. J. Med. Chem. 44, 1313–1333.

    Article  Google Scholar 

  12. Schneider, G. and Nettekoven, M. (2003) Ligand-based combinatorial design of selective purinergic receptor (A2A) antagonists using self-organizing maps. J. Comb. Chem. 5, 233–237.

    Article  PubMed  CAS  Google Scholar 

  13. McGregor, M. J. and Muskal, S. M. (2000) Pharmacophore fingerprinting. 2. Application to primary library design. J. Chem. Inf. Comput. Sci. 40, 11–125.

    Google Scholar 

  14. Schuffenhauer, A., Zimmermann, J., Stoop, R., van der Vyver, J.-J., Lecchini, S., and Jacoby, E. (2002) An ontology for pharmaceutical ligands and its application for in silico screening and library design. J. Chem. Inf. Comput. Sci. 42, 947–955.

    PubMed  CAS  Google Scholar 

  15. Naumann, T. and Matter, H. (2002) Structural classification of protein kinases using 3d molecular interaction field analysis of their ligand binding sites: Target family landscapes. J. Med. Chem. 45, 2366–2378.

    Article  PubMed  CAS  Google Scholar 

  16. Klabunde, T. and Hessler, G. (2002) Drug design strategies for targeting G-protein coupled receptors. Chembiochem 3, 929–944.

    Google Scholar 

  17. Daylight Chemical Information Systems, Inc., 27401 Los Altos, Suite 360, Mission Viejo, CA 92691.

    Google Scholar 

  18. Carhart, R. E., Smith, D. H., and Venkataraghavan, R. (1985) Atom pairs as molecular features in structure-activity studies: definition and applications. J. Chem. Inf. Comput. Sci. 25, 64–73.

    CAS  Google Scholar 

  19. McGregor, M. J. and Muskal, S. M. (1999) Pharmacophore fingerprinting. 1. Application to QSAR and focused library design. J. Chem. Inf. Comput. Sci. 39, 569–574.

    PubMed  CAS  Google Scholar 

  20. Mason, J. S., Morize, I., Menard, P. R. Cheney, D. L., Hulme, C., and Labaudiniere, R. F. (1999) New 4-point pharmacophore method for molecular similarity and diversity applications: overview of the method and applications, including a novel approach to the design of combinatorial libraries containing privileged substructures. J. Med. Chem. 42, 3251–3264.

    Article  PubMed  CAS  Google Scholar 

  21. Beno, B. R. and Mason, J. S. (2001) The design of combinatorial libraries using properties and 3D pharmacophore fingerprints. Drug Disc. Today 6, 251–258.

    Article  CAS  Google Scholar 

  22. Pearlman, R. S. (1996) Novel software tools for addressing chemical diversity, Network Science, http://www.awod.com/netsci/Science/combichem/feature08.html.

  23. Mason, J. S., Good, A. C., and Martin, E.J. (2001) 3-D pharmacophores in drug discovery. Curr. Pharm. Design 7, 567–597.

    Article  CAS  Google Scholar 

  24. Willett, P., Barnard, J. M., and Downs, G. M. (1998) Chemical similarity searching. J. Chem. Inf. Comput. Sci. 38, 983–996.

    CAS  Google Scholar 

  25. Ugi, I. and Steinbruckner, C. (1961) Isonitriles. II. Reaction of isonitriles with carbonyl compounds, amines, and hydrazoic acid. Chem. Ber. 94, 734–742.

    Article  CAS  Google Scholar 

  26. MDL Drug Data Report, MDL Information Systems, San Leandro, CA, USA.

    Google Scholar 

  27. Lamb, M. L., Bradley E. K., Spellmeyer, D. C., Suto, M. J., and Grootenhuis, P. D. J. Iterative design of gene-family directed screening libraries. Book of Abstracts, 222nd ACS National Meeting, Chicago, Aug 26–30, 2001.

    Google Scholar 

  28. Good, A. C. and Lewis, R. A. (1997) New methodology for profiling combinatorial libraries and screening sets: cleaning up the design process with HARPick. J. Med. Chem. 40, 3926–3936.

    Article  PubMed  CAS  Google Scholar 

  29. Bradley, E. K., Beroza, P., Penzotti, J. E, Grootenhuis, P. D. J., Spellmeyer, D. C., and Miller, J. L. (2000) A rapid computational method for lead evolution: description and application to α1-adrenergic antagonists. J. Med. Chem. 43, 2770–2774.

    Article  PubMed  CAS  Google Scholar 

  30. Zuckerman, R. N., Martin, E. J., Spellmeyer, D. C., et al. (1994) Discovery of nanomolar ligands for 7-transmembrane G-protein-coupled receptors from a diverse N-(substituted)glycine peptoid library. J. Med. Chem. 37, 2678–2685.

    Article  Google Scholar 

  31. Beno, B. R. and Mason, J. S. Combinatorial library design using both properties and 3D pharmacophore fingerprints. Book of Abstracts, 221st ACS National Meeting, San Diego, 2001.

    Google Scholar 

  32. Pickett, S. D., McLay, I. M., abd Clark, D. E. (2000) Enhancing the hit-to-lead properties of lead optimization libraries. J. Chem. Inf. Comput. Sci. 40, 263–272.

    PubMed  CAS  Google Scholar 

  33. Mason, J. S. and Beno, B. R. (2000) Library design using BCUT chemistry-space descriptors and multiple four-point pharmacophore fingerprints: Simultaneous optimization and structure-based diversity. J. Mol. Graphics Model. 18, 438–451.

    Article  CAS  Google Scholar 

  34. Murray, C. M. and Cato, S. J. (1999) Design of libraries to explore receptor sites. J. Chem. Inf. Comput. Sci. 39, 46–50.

    PubMed  CAS  Google Scholar 

  35. Eksterowicz, J. E., Evensen, E., Lemmen, C., et al. (2002) Coupling structure-based design with combinatorial chemistry: application of active site derived pharmacophores with informative library design. J. Mol. Graph. Model. 20, 469–477.

    Article  PubMed  CAS  Google Scholar 

  36. Penzotti, J. E., Lamb, M. L, Evensen, E., and Grootenhuis, P. D. J. (2002) A computational ensemble model for identifying substrates of P-glycoprotein. J. Med. Chem. 45, 1737–1740.

    Article  PubMed  CAS  Google Scholar 

  37. Ekins, S., Bravi, G., Binkley, S., et al. (1999) Three-and four-dimensional quantitative structure activity relationship analyses of cytochrome P-450 3A4 inhibitors. J. Pharm. Exp. Ther. 290, 429–438.

    CAS  Google Scholar 

  38. Ekins, S., Bravi, G., Wikel, J. H., and Wrighton, S.A. (1999) Three-dimensional-quantitative structure activity relationship analysis of cytochrome P-450 3A4 substrates. J. Pharm. Exp. Ther. 291, 424–433.

    CAS  Google Scholar 

  39. Bemis, G. W. and Murcko, M. A. (1996) The properties of known drugs. 1. Molecular frameworks. J. Med. Chem. 39, 2887–2893.

    Article  PubMed  CAS  Google Scholar 

  40. The SYBYL modeling package is available from Tripos Associates, St Louis, MO.

    Google Scholar 

  41. Vaz, R., private communication, 1999.

    Google Scholar 

  42. ClassPharmer™ is available from Bioreason, Inc., Santa Fe, NM.

    Google Scholar 

  43. Schnur, D. M. and Hermsmeier, M., Recent approaches to target class design, 36th MARM of the ACS, 2003.

    Google Scholar 

  44. Schnur, D. and Venkatarangan, P. (2001) Applications of cell-based diversity methods to combinatorial library design. In Combinatorial library design and evaluation, Ghose, A. K. and Viswadhan, V. N. (eds.), Marcel Dekker, Inc., New York, NY.

    Google Scholar 

  45. DiverseSolutions was developed by R. S. Pearlman and K. M. Smith at the University of Texas at Austin and is distributed by Optive Research, Inc. http://www.optive.com, and Tripos Inc., http://www.tripos.com.

  46. Schnur, D. (1999) Design and diversity analysis of large combinatorial libraries using cell-based methods. J. Chem. Inf. Comput. Sci. 39, 36–45.

    CAS  Google Scholar 

  47. Pearlman, R. S. and Smith, K. M. (1999) Metric validation and the receptor-relevant subspace concept. J. Chem. Inf. Comput. Sci. 39, 28–35.

    CAS  Google Scholar 

  48. Schnur, D. M. (2001) Approaches to target class library design, CHI Conference on Molecular Diversity, San Diego, CA.

    Google Scholar 

  49. Stewart, E. L., Brown, P. J., Bentley, J. A., and Wilson, T. M. (2001) Abstracts of Papers, 222nd ACS National Meeting, Chicago, IL, August 26–30.

    Google Scholar 

  50. LibraryMaker and LibraryDesigner are distributed by Optive Research, Austin, TX; http://www.optiveresearch.com.

  51. Wang, X. and Saunders, J. (2001) Abstracts of Papers, 222nd ACS National Meeting, Chicago, IL, August 26–30.

    Google Scholar 

  52. Beno, B. R. and Mason, J. S., unpublished.

    Google Scholar 

  53. Pirard, B. and Pickett, S. D. (2000) Classification of kinase inhibitors using BCUT descriptors. J. Chem. Inf. Comput. Sci. 40, 1431–1440.

    PubMed  CAS  Google Scholar 

  54. Manallack, D. T., Pitt, W. R., Gancia, E., et al. (2002) Selecting screening candidates for kinase and G-protein-coupled receptor targets using neural networks. J. Chem. Inf. Comput. Sci. 42, 1256–1262.

    PubMed  CAS  Google Scholar 

  55. Sitkoff, D. F., Krystek, S. R., Bassolino, D. A., et al. (2001) Protein family clustering as an aid to drug design. Abstr. Pap. Am. Chem. Soc. 221st, COMP-161.

    Google Scholar 

  56. Montelione, G. T. (2001) Structural genomics: an approach to the protein folding problem. Proc. Natl. Acad. Sci. USA 98, 13,488–13,489.

    Article  PubMed  CAS  Google Scholar 

  57. Peitsch, M. C., Schwede, T., Diemand, A., and Guex, N. (2002) Protein structure prediction by comparison: homology-based modeling. Current Topics in Computational Molecular Biology, 449–466.

    Google Scholar 

  58. Bohm, H.-J. (2001) Progress in structure-based library design. In Rational approaches to drug design: Proceedings of the 13th European Symposium on QSAR, Höltje, H.-D. and Sippl, W. (eds.), Prous Science, Barcelona, pp. 367–371.

    Google Scholar 

  59. Stahl, M. (2000) Structure-based library design. Meth. Prin. Med. Chem. 10, 229–264.

    CAS  Google Scholar 

  60. Leach, A. R., Bryce, R. A., and Robinson, A. J. (2000) Synergy between combinatorial chemistry and de novo design. J. Mol. Graph. Model. 18, 358–367.

    Article  PubMed  CAS  Google Scholar 

  61. Gray, N. S., Wodicka, L., Thunnissen, A.-M. W. H., et al. (1998) Exploiting chemical libraries, structure, and genomics in the search for kinase inhibitors. Science 281, 533–538.

    Article  PubMed  CAS  Google Scholar 

  62. Gehlhaar, D. K., Bouzida, D., and Rejto, P. A. (1999) Reduced dimensionality in ligand-protein structure prediction: covalent inhibitors of serine proteases and design of site-directed combinatorial libraries. ACS Symposium Series 719, 292–311.

    Article  CAS  Google Scholar 

  63. Honma, T. Hayashi, K., Aoyama, T., et al. (2001) Structure-based generation of a new class of potent cdk4 inhibitors: new de novo design strategy and library design. J. Med. Chem. 44, 4615–4627.

    Article  PubMed  CAS  Google Scholar 

  64. Honma, T., Yoshizumi, T., Hashimoto, N., et al. (2001) A novel approach for the development of selective Cdk4 inhibitors: library design based on locations of Cdk4 specific amino acid residues. J. Med. Chem. 44, 4628–4640.

    Article  PubMed  CAS  Google Scholar 

  65. Diller, D. J. (2001) Homology models, high throughput docking, and drug design. Molecular modeling. Abstr. Pap. Am. Chem. Soc. 222nd, COMP-050.

    Google Scholar 

  66. Sippl, W. (2002) GPCR Dopamine D3 antagonist design, in Proceedings of the 14th European symposium on QSAR, Livingstone, D. and Ford, M. (eds.), Wiley-VCH, Basel. http://www.iainm.demon.co.uk/euroqsarws2.htm.

    Google Scholar 

  67. GRID version 18, Molecular Discovery Ltd., West Way House, Elms Parade, Oxford UK.

    Google Scholar 

  68. Clark, M., Cramer, R. D., Jones, D. M., Patterson, D. E., and Simeroth, P. E. (1990) Comparative molecular field analysis (CoMFA). 2. Towards its use with 3D-structural databases. Tetrahedron Comput. Methodol. 3, 47–59.

    Article  CAS  Google Scholar 

  69. Klebe, G., Abraham, U., and Mietzner, T. (1994) Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. J. Med. Chem. 37, 4130–4146.

    Article  PubMed  CAS  Google Scholar 

  70. Good, A. C., Cheney, D. L., Sitkoff, D. F., et al. (2003) Analysis and optimization of structure-based virtual screening protocols (2). Examination of docked ligand orientation sampling methodology; mapping a pharmacophore for success. J. Mol. Graph. Mod. 22, 31–40.

    Article  CAS  Google Scholar 

  71. Engh, Richard A. and Bossemeyer, D. (2002) Structural aspects of protein kinase control—role of conformational flexibility. Pharmacol. Therapeut. 93, 99–111.

    Article  CAS  Google Scholar 

  72. GOLD version 1.2, developed and distributed by the CCDC, 12 Union Road, Cambridge, CB2 1EZ, UK. URL: http://www.ccdc.cam.ac.uk/prods/gold/index.html.

  73. DOCK, developed and distributed by the Kuntz group, Dept. of Pharmaceutical Chemistry, 512 Parnassus, University of California, San Francisco, CA, USA. URL: http://www.cmpharm.ucsf.edu/kuntz.

  74. Baxter, C. A., Murray, C. W., Waszkowycz, B., et al. (2000) New approach to molecular docking and its application to virtual screening of chemical databases. J. Chem. Inf. Comput. Sci. 40, 254–262.

    PubMed  CAS  Google Scholar 

  75. Furet, P., Meyer, T., Strauss, A., Raccuglia, S., and Rondeau, J-M. (2002) Structure-based design and protein X-ray analysis of a protein kinase inhibitor. Bioorg. Med. Chem. Lett. 12, 221–224.

    Article  PubMed  CAS  Google Scholar 

  76. Balakin, K. V., Tkachenko S. E., Lang, S. A., Okun, I., Ivashchenko, A. A., and Savchuk, N. P. (2002) Property-based design of GPCR-targeted library. J. Chem. Inf. Comput. Sci. 42, 1332–1342.

    PubMed  CAS  Google Scholar 

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Authors and Affiliations

  1. Computer Aided Drug Design, Pharmaceutical Research Institute, Bristol-Myers Squibb Company, Princeton, New Jersey, USA

    Dora Schnur, Brett R. Beno, Andrew Good & Andrew Tebben

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  1. Dora Schnur
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  2. Brett R. Beno
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  3. Andrew Good
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  4. Andrew Tebben
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Editors and Affiliations

  1. Albany Molecular Research Inc., Bothell Research Center, Bothell, WA

    Jürgen Bajorath

  2. University of Washington, Seattle, WA

    Jürgen Bajorath

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© 2004 Humana Press Inc.

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Schnur, D., Beno, B.R., Good, A., Tebben, A. (2004). Approaches to Target Class Combinatorial Library Design. In: Bajorath, J. (eds) Chemoinformatics. Methods in Molecular Biology™, vol 275. Humana Press. https://doi.org/10.1385/1-59259-802-1:355

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  • DOI: https://doi.org/10.1385/1-59259-802-1:355

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-261-2

  • Online ISBN: 978-1-59259-802-1

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