Skip to main content
SpringerLink
Log in
Menu
Find a journal Publish with us
Search
Cart
  1. Home
  2. Molecular Diversity
  3. Article

Design of chemical libraries with potentially bioactive molecules applying a maximum common substructure concept

  • Full-Length Paper
  • Open access
  • Published: 15 August 2009
  • volume 14, pages 401–408 (2010)
Download PDF

You have full access to this open access article

Molecular Diversity Aims and scope Submit manuscript
Design of chemical libraries with potentially bioactive molecules applying a maximum common substructure concept
Download PDF
  • Michael Lisurek1,
  • Bernd Rupp1,
  • Jörg Wichard1,
  • Martin Neuenschwander1,
  • Jens Peter von Kries1,
  • Ronald Frank2,
  • Jörg Rademann1,3 &
  • …
  • Ronald Kühne1 
  • 1622 Accesses

  • 57 Citations

  • 10 Altmetric

  • Explore all metrics

Cite this article

Abstract

Success in small molecule screening relies heavily on the preselection of compounds. Here, we present a strategy for the enrichment of chemical libraries with potentially bioactive compounds integrating the collected knowledge of medicinal chemistry. Employing a genetic algorithm, substructures typically occurring in bioactive compounds were identified using the World Drug Index. Availability of compounds containing the selected substructures was analysed in vendor libraries, and the substructure-specific sublibraries were assembled. Compounds containing reactive, undesired functional groups were omitted. Using a diversity filter for both physico-chemical properties and the substructure composition, the compounds of all the sublibraries were ranked. Accordingly, a screening collection of 16,671 compounds was selected. Diversity and chemical space coverage of the collection indicate that it is highly diverse and well-placed in the chemical space spanned by bioactive compounds. Furthermore, secondary assay-validated hits presented in this study show the practical relevance of our library design strategy.

Article PDF

Download to read the full article text

Use our pre-submission checklist

Avoid common mistakes on your manuscript.

References

  1. Villar HO, Koehler RT (2000) Comments on the design of chemical libraries for screening. Mol Divers 5: 13–24. doi:10.1023/A:1011326914800

    Article  CAS  PubMed  Google Scholar 

  2. Miller JL (2006) Recent developments in focused library design: targeting gene-families. Curr Top Med Chem 6: 19–29

    Article  CAS  PubMed  Google Scholar 

  3. Irwin JJ (2006) How good is your screening library. Curr Opin Chem Biol 10: 352–356. doi:10.1016/j.cbpa.2006.06.003

    Article  CAS  PubMed  Google Scholar 

  4. Xue L, Bajorath J (2000) Molecular descriptors for effective classification of biologically active compounds based on principal component analysis identified by a genetic algorithm. J Chem Inf Comput Sci 40: 801–809. doi:10.1021/ci000322m

    CAS  PubMed  Google Scholar 

  5. Brenk R, Schipani A, James D, Krasowski A, Gilbert IH, Frearson J, Wyatt PG (2008) Lessons learnt from assembling screening libraries for drug discovery for neglected diseases. ChemMedChem 3: 435–444. doi:10.1002/cmdc.200700139

    Article  CAS  PubMed  Google Scholar 

  6. Zartler ER, Shapiro MJ (2005) Fragonomics: fragment-based drug discovery. Curr Opin Chem Biol 9: 366–370. doi:10.1016/j.cbpa.2005.05.002

    Article  CAS  PubMed  Google Scholar 

  7. Hartshorn MJ, Murray CW, Cleasby A, Frederickson M, Tickle IJ, Jhoti H (2005) Fragment-based lead discovery using X-ray crystallography. J Med Chem 48: 403–413. doi:10.1021/jm0495778

    Article  CAS  PubMed  Google Scholar 

  8. Jacoby E, Davies J, Blommers MJ (2003) Design of small molecule libraries for NMR screening and other applications in drug discovery. Curr Top Med Chem 3: 11–23. doi:10.2174/1568026033392606

    Article  CAS  PubMed  Google Scholar 

  9. Schmidt MF, Isidro-Llobet A, Lisurek M, El-Dahshan A, Tan J, Hilgenfeld R, Rademann J (2008) Sensitized detection of inhibitory fragments and iterative development of non-peptidic protease inhibitors by dynamic ligation screening. Angew Chem Int Ed Engl 47: 3275–3278. doi:10.1002/anie.200704594

    Article  CAS  PubMed  Google Scholar 

  10. Bemis GW, Murcko MA (1996) The properties of known drugs. 1. Molecular frameworks. J Med Chem 39: 2887–2893. doi:10.1021/jm9602928

    Article  CAS  PubMed  Google Scholar 

  11. Xu YJ, Johnson M (2002) Using molecular equivalence numbers to visually explore structural features that distinguish chemical libraries. J Chem Inf Comput Sci 42: 912–926. doi:10.1021/ci025535l

    CAS  PubMed  Google Scholar 

  12. Martin YC (1990) Computer design of potentially bioactive molecules by geometric searching with ALADDIN. Tetrahedron Comput Methodol 3: 15–25. doi:10.1016/0898-5529(90)90117-Q

    Article  CAS  Google Scholar 

  13. Martin YC (1992) 3D database searching in drug design. J Med Chem 35: 2145–2154. doi:10.1021/jm00090a001

    Article  CAS  PubMed  Google Scholar 

  14. Abel U, Koch C, Speitling M, Hansske FG (2002) Modern methods to produce natural-product libraries. Curr Opin Chem Biol 6: 453–458. doi:10.1016/S1367-5931(02)00338-1

    Article  CAS  PubMed  Google Scholar 

  15. Koch MA, Schuffenhauer A, Scheck M, Wetzel S, Casaulta M, Odermatt A, Ertl P, Waldmann H (2005) Charting biologically relevant chemical space: a structural classification of natural products (SCONP). Proc Natl Acad Sci USA 102: 17272–17277. doi:10.1073/pnas.0503647102

    Article  CAS  PubMed  Google Scholar 

  16. Wagener M, Gasteiger J (1994) The determination of maximum common substructures by a genetic algorithm: application in synthesis design and for the structural analysis of biological activity. Angew Chem Int Ed Engl 33: 1189–1192. doi:10.1002/anie.199411891

    Article  Google Scholar 

  17. Evans BE, Rittle KE, Bock MG, DiPardo RM, Freidinger RM, Whiter WL, Lundell GF, Veber DF, Anderson PS, Chang RSL, Lotti VJ, Cerino DJ, Chen TB, Kling PJ, Kunkel KA, Springer JP, Hirshfield J (1988) Methods for drug discovery: development of potent, selective, orally effective cholecystokinin antagonists. J Med Chem 31: 2235–2246. doi:10.1021/jm00120a002

    Article  CAS  PubMed  Google Scholar 

  18. Patchett AA, Nargund RP (2000) Privileged structures—an update. Annu Rep Med Chem 35: 289–298. doi:10.1016/S0065-7743(00)35027-8

    Article  CAS  Google Scholar 

  19. Schnur DM, Hermsmeier MA, Tebben AJ (2006) Are target- family-privileged substructures truly privileged. J Med Chem 49: 2000–2009. doi:10.1021/jm0502900

    Article  CAS  PubMed  Google Scholar 

  20. WDI, Derwent World Drug Index, Release 2005, Derwent Information Ltd., London

  21. ChemDiv Inc., ChemDiv Chemical Database, http://www.chemdiv.com, 6605 Nancy Ridge Drive, San Diego, CA, 92121, USA

  22. MOE Molecular Operating Environment, version 2005.06, Chemical Computing Group Inc., Montreal, Quebec, Canada

  23. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 23: 3–25. doi:10.1016/S0169-409X(96)00423-1

    Article  CAS  Google Scholar 

  24. Labute P (2000) A widely applicable set of descriptors. J Mol Graph Model 18: 464–477. doi:10.1016/S1093-3263(00)00068-1

    Article  CAS  PubMed  Google Scholar 

  25. ChemACX, CambridgeSoft, http://www.chemacx.com, 100 CambridgePark Drive, Cambridge, MA, 02140, USA

  26. Dictionary of Natural Products, version 14.1 (2005). Chapman & Hall/CRC Informa, London

Download references

Acknowledgements

We thank Hans-Dieter Höltje and Victoria Higman for critical reading of the manuscript. The screening data were provided by Jörn Saupe, Samuel Beligny, Svantje Behnken and Susann Matthes. Three institutes, namely the Helmholtz Centre for Infection Research (HZI), the Max Delbrück Centrum (MDC), and the Leibniz Institut für Molekulare Pharmakologie (FMP) co-financed the described screening library, which is now ready to use for supporting screening projects. Extensions to this library are currently made by the MPI in Dortmund, the University of Oslo and the University of Konstanz.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Author information

Authors and Affiliations

  1. FMP Leibniz Institut für Molekulare Pharmakologie, Robert-Roessle Straße 10, 13125, Berlin, Germany

    Michael Lisurek, Bernd Rupp, Jörg Wichard, Martin Neuenschwander, Jens Peter von Kries, Jörg Rademann & Ronald Kühne

  2. Department of Chemical Biology, HZI Helmholz Centre for Infection Research, Inhoffenstraße 7, 38124, Braunschweig, Germany

    Ronald Frank

  3. Institut für Chemie und Biochemie, Freie Universität Berlin, Takusstraße 3, 14195, Berlin, Germany

    Jörg Rademann

Authors
  1. Michael Lisurek
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bernd Rupp
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jörg Wichard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Martin Neuenschwander
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jens Peter von Kries
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ronald Frank
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jörg Rademann
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ronald Kühne
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jörg Rademann or Ronald Kühne.

Electronic Supplementary Material

The Below is the Electronic Supplementary Material.

DOC 1 (DOC 422 KB)

Rights and permissions

Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Reprints and Permissions

About this article

Cite this article

Lisurek, M., Rupp, B., Wichard, J. et al. Design of chemical libraries with potentially bioactive molecules applying a maximum common substructure concept. Mol Divers 14, 401–408 (2010). https://doi.org/10.1007/s11030-009-9187-z

Download citation

  • Received: 22 April 2009

  • Accepted: 26 July 2009

  • Published: 15 August 2009

  • Issue Date: May 2010

  • DOI: https://doi.org/10.1007/s11030-009-9187-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Bio informatics
  • Drug design
  • High throughput screening
  • Library design
  • Molecular diversity
Use our pre-submission checklist

Avoid common mistakes on your manuscript.

Advertisement

search

Navigation

  • Find a journal
  • Publish with us

Discover content

  • Journals A-Z
  • Books A-Z

Publish with us

  • Publish your research
  • Open access publishing

Products and services

  • Our products
  • Librarians
  • Societies
  • Partners and advertisers

Our imprints

  • Springer
  • Nature Portfolio
  • BMC
  • Palgrave Macmillan
  • Apress
  • Your US state privacy rights
  • Accessibility statement
  • Terms and conditions
  • Privacy policy
  • Help and support

Not affiliated

Springer Nature

© 2023 Springer Nature