Advertisement

Protein Kinase Selectivity Profiling Using Microfluid Mobility Shift Assays

  • Peter DrueckesEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1439)

Abstract

Biochemical selectivity profiling is an integral part of early drug development. Typically compounds from optimization phase are regularly tested for off-target activities within or across target families. This article presents workflow and critical aspects of biochemical protein kinase profiling based on microfluidic mobility shift assays.

Key words

Kinase Selectivity profiling Microfluidic mobility shift assay Compound preparation 

Notes

Acknowledgment

I would like to thank Shin Numao and Patrik Roethlisberger for their helpful input to the manuscript. I would like to thank Joerg Trappe for suggesting and encouraging the drafting of this manuscript.

References

  1. 1.
    Fischer EH, Krebs EG (1955) Conversion of phosphorylase b to phosphorylase a in muscle extracts. J Biol Chem 216:121–132Google Scholar
  2. 2.
    Krebs EG, Kent AB, Fischer EH (1958) The muscle phosphorylase b kinase reaction. J Biol Chem 231:73–83Google Scholar
  3. 3.
    Klebl B, Müller G, Hamacher M (2011) Protein kinases as drug targets. Methods and principles in medicinal chemistry, vol 49. Wiley, New York, NYCrossRefGoogle Scholar
  4. 4.
    Cohen P (2002) Protein kinases - the major drug targets of the twenty-first century? Nat Rev Drug Discov 1:309–315CrossRefGoogle Scholar
  5. 5.
    Wu P, Nielsen ET, Clausen MH (2015) FDA-approved small-molecule kinase inhibitors. Trends Pharmacol Sci 36(7):422–439CrossRefGoogle Scholar
  6. 6.
    Comley J (2013) Outsourced kinase profiling services - adding value to in-house kinase programmes. Drug Discov World Fall 2013:26–45Google Scholar
  7. 7.
    Ma H, Deacon S, Horiuchi K (2008) The challenge of selecting protein kinase assays for lead discovery optimization. Exp Opin Drug Discov 3(6):607–621CrossRefGoogle Scholar
  8. 8.
    Li H (2009) Review of biochemical assays for protein kinase drug discovery. Trends Bio/Pharmaceutical Ind 5(1):24–32Google Scholar
  9. 9.
    Chène P (2008) Challenges in design of biochemical assays for the identification of small molecules to target multiple conformations of protein kinases. Drug Discov Today 13(11/12):522–529CrossRefGoogle Scholar
  10. 10.
    Heedmann B, Klumpp M (2015) Screening for inhibitors of kinase autophosphorylation. In: Janzen WP (ed) High throughput screening: methods and protocols, 3rd edn. Springer, New York, NYGoogle Scholar
  11. 11.
    Cohen CB, Chin-Dixon E, Jeong S, Nikiforov TT (1999) A microchip-based enzyme assay for protein kinase A. Anal Biochem 273:89–97CrossRefGoogle Scholar
  12. 12.
    Perrin D, Frémaux C, Shutes A (2010) Capillary microfluidic electrophoretic mobility shift assays: application to enzymatic assays in drug discovery. Exp Opin Drug Discov 5(1):51–61CrossRefGoogle Scholar
  13. 13.
    Miletti F, Hermann JC (2012) Targeted kinase selectivity from kinase profiling data. Med Chem Lett 3:383–386CrossRefGoogle Scholar
  14. 14.
    Niijima S, Shiraishi A, Okuno Y (2012) Dissecting kinase profiling data to predict activity and understand cross-reactivity of kinase inhibitors. J Chem Inf Model 52:901–912CrossRefGoogle Scholar
  15. 15.
    Jacoby E, Tresadern G, Bembenek S, Wroblowski B, Buyck C, Neef J-M, Rassokhin D, Poncelet A, Hunt J, van Vlijmen H (2015) Extending kinome coverage by analysis of kinase inhibitor broad profiling data. Drug Discov Today 20(6):652–658CrossRefGoogle Scholar
  16. 16.
    Normolle DP (1993) An algorithm for robust non-linear analysis of radioimmunoassay and other bioassays. Stat Med 12:2025–2042CrossRefGoogle Scholar
  17. 17.
    Formenko I, Durst M, Balaban D (2006) Robust Regression for high-throughput screening. Comput Methods Programs Biomed 82:31–37CrossRefGoogle Scholar
  18. 18.
    Sebaugh JL (2011) Guidelines for accurate EC50/IC50 estimation. Pharm Stat 10:128–134. doi: 10.1002/pst.426, http://onlinelibrary.wiley.com/doi/ 10.1002/pst.426/pdf CrossRefGoogle Scholar
  19. 19.
    Kelly C, Rice J (1990) Monotone smoothing with application to dose-response curves and the assessment of synergism. Biometrics 46(4):1071–1085CrossRefGoogle Scholar
  20. 20.
    Kahm M, Hasenbrink G, Lichtenberg-Frate H, Ludwig J, Kschischo M (2010) grofit: fitting biological growth curves with R. J Stat Softw 33(7):1–21CrossRefGoogle Scholar
  21. 21.
    Zhang JH, Chung TDY, Oldenburg KR (1999) A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J Biomol Screen 4:67–73CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.CPC Screening Sciences, Novartis Pharma AGNovartis Institutes for Biomedical ResearchBaselSwitzerland

Personalised recommendations