Advertisement

Mapping Biological Activities to Different Types of Molecular Scaffolds: Exemplary Application to Protein Kinase Inhibitors

  • Dilyana Dimova
  • Jürgen BajorathEmail author
Protocol
  • 852 Downloads
Part of the Methods in Molecular Biology book series (MIMB, volume 1825)

Abstract

Scaffolds were originally introduced to delineate core structures of active compounds. They are also used to assess the ability of computational methods to identify structurally diverse active compounds. Biological activities of compound series are often mapped to scaffolds. This is done to better understand activity distributions over different structural classes or search for core structures of compounds that are preferentially active against target families of interest. Herein, we describe in detail how such scaffold activity profiles are generated and compare profiles for differently defined scaffolds. As an exemplary application, scaffolds of currently available kinase inhibitors covering the human kinome are analyzed.

Key words

Bioactive compounds Scaffolds Core structures Scaffold–activity relationships Kinase inhibitors Compound promiscuity 

Notes

Acknowledgment

We thank OpenEye Scientific Software, Inc. for a free academic license of the OpenEye Toolkits.

References

  1. 1.
    Hu Y, Stumpfe D, Bajorath J (2011) Lessons learned from molecular scaffold analysis. J Chem Inf Model 51:1743–1752Google Scholar
  2. 2.
    Hu Y, Stumpfe D, Bajorath J (2016) Computational exploration of molecular scaffolds in medicinal chemistry. J Med Chem 59:4062–4076CrossRefGoogle Scholar
  3. 3.
    Bemis GW, Murcko MA (1996) The properties of known drugs. 1. Molecular frameworks. J Med Chem 39:2887–2893CrossRefGoogle Scholar
  4. 4.
    Dimova D, Stumpfe D, Hu Y, Bajorath J (2016) Analog series-based scaffolds: computational design and exploration of a new type of molecular scaffolds for medicinal chemistry. Future Sci OA 2:FSO149CrossRefGoogle Scholar
  5. 5.
    Schneider G, Neidhart W, Giller T, Schmid G (1999) “Scaffold-hopping” by topological pharmacophore search: a contribution to virtual screening. Angew Chem Int Ed 38(19):2894–2896CrossRefGoogle Scholar
  6. 6.
    Schuffenhauer A (2012) Computational methods for scaffold hopping. Wires Comput Mol Sci 2:842–867CrossRefGoogle Scholar
  7. 7.
    Evans BE, Rittle KE, Bock MG, DiPardo RM, Freidinger RM, Whitter WL et al (1988) Methods for drug discovery: development of potent, selective, orally effective cholecystokinin antagonists. J Med Chem 31:2235–2246CrossRefGoogle Scholar
  8. 8.
    Müller G (2003) Medicinal chemistry of target family-directed masterkeys. Drug Discov Today 8:681–691CrossRefGoogle Scholar
  9. 9.
    Welsch ME, Snyder SA, Stockwell BR (2010) Privileged scaffolds for library design and drug discovery. Curr Opin Chem Biol 14:347–361CrossRefGoogle Scholar
  10. 10.
    Hu Y, Bajorath J (2010) Molecular scaffolds with high propensity to form multi-target activity cliffs. J Chem Inf Model 50:500–510CrossRefGoogle Scholar
  11. 11.
    Hu Y, Bajorath J (2015) Exploring the scaffold universe of kinase inhibitors. J Med Chem 58:315–332CrossRefGoogle Scholar
  12. 12.
    Hu Y, Bajorath J (2013) Compound promiscuity—what can we learn from current data. Drug Discov Today 18:644–650CrossRefGoogle Scholar
  13. 13.
    Hu Y, Bajorath J (2013) High-resolution view of compound promiscuity. F1000Res 2:144PubMedPubMedCentralGoogle Scholar
  14. 14.
    Gaulton A, Bellis LJ, Bento AP, Chambers J, Davies M, Hersey A et al (2012) ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res 40:D1100–D1107CrossRefGoogle Scholar
  15. 15.
    Hu Y, Bajorath J (2017) SAR matrix method for large-scale analysis of compound structure-activity relationships and exploration of multi-target activity spaces (accompanying chapter). In: Brown JB (ed) Computational chemogenomics. Springer, New YorkGoogle Scholar
  16. 16.
    Kenny PW, Sadowski J (2004) Structure modification in chemical databases. In: Oprea TI (ed) Chemoinformatics in drug discovery. Wiley-VCH, Weinheim, pp 271–285Google Scholar
  17. 17.
    Lewell XQ, Judd DB, Watson SP, Hann MM (1998) RECAP – retrosynthetic combinatorial analysis procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. J Chem Inf Comput Sci 38:511–522CrossRefGoogle Scholar
  18. 18.
    de la Vega de León A, Bajorath J (2014) Matched molecular pairs derived by retrosynthetic fragmentation. Med Chem Commun 5:64–67CrossRefGoogle Scholar
  19. 19.
    OEChem version 1.7.7 (2012) OpenEye Scientific Software, Inc., Santa Fe, NM. http://www.eyesopen.com

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal ChemistryRheinische Friedrich-Wilhelms-UniversitätBonnGermany

Personalised recommendations