Advertisement

Drug Affinity Responsive Target Stability (DARTS) for Small-Molecule Target Identification

Protocol
First Online:
Part of the Methods in Molecular Biology book series (MIMB, volume 1263)

Abstract

Drug affinity responsive target stability (DARTS) is a relatively quick and straightforward approach to identify potential protein targets for small molecules. It relies on the protection against proteolysis conferred on the target protein by interaction with a small molecule. The greatest advantage of this method is being able to use the native small molecule without having to immobilize or modify it (e.g., by incorporation of biotin, fluorescent, radioisotope, or photoaffinity labels). Here we describe in detail the protocol for performing unbiased DARTS with complex protein lysates to identify binding targets of small molecules and for using DARTS-Western blotting to test, screen, or validate potential small-molecule targets. Although the ideas have mainly been developed from studying molecules in areas of biology that are currently of interest to us and our collaborators, the general principles should be applicable to the analysis of all molecules in nature.

Key words

Small molecules Drugs Target identification Metabolites Natural products Proteomics Mass spectrometry Immunoblotting 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

Supported by the US National Institutes of Health grants R01 CA124974 (J.H.), R21 CA149774 (J.H.), U19 AI067769 (W.B.), R01 GM103479 (J.A.L.), R01 GM104610 (J.A.L.), and training grants to M.Y.P. (T32 GM007185) and B.L. (T32 CA009120).

References

  1. 1.
    O'Connor CJ, Laraia L, Spring DR (2011) Chemical genetics. Chem Soc Rev 40:4332–4345PubMedCrossRefGoogle Scholar
  2. 2.
    Yang GX, Li X, Snyder M (2012) Investigating metabolite-protein interactions: an overview of available techniques. Methods 57:459–466PubMedCentralPubMedCrossRefGoogle Scholar
  3. 3.
    McFedries A, Schwaid A, Saghatelian A (2013) Methods for the elucidation of protein-small molecule interactions. Chem Biol 20:667–673PubMedCrossRefGoogle Scholar
  4. 4.
    Rask-Andersen M, Masuram S, Schioth HB (2014) The druggable genome: evaluation of drug targets in clinical trials suggests major shifts in molecular class and indication. Annu Rev Pharmacol Toxicol 54:9–26PubMedCrossRefGoogle Scholar
  5. 5.
    Lomenick B, Olsen RW, Huang J (2011) Identification of direct protein targets of small molecules. ACS Chem Biol 6:34–46PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Ong SE et al (2012) Identifying cellular targets of small-molecule probes and drugs with biochemical enrichment and SILAC. Methods Mol Biol 803:129–140PubMedCrossRefGoogle Scholar
  7. 7.
    Ziegler S et al (2013) Target identification for small bioactive molecules: finding the needle in the haystack. Angew Chem Int Ed Engl 52:2744–2792PubMedCrossRefGoogle Scholar
  8. 8.
    Futamura Y, Muroi M, Osada H (2013) Target identification of small molecules based on chemical biology approaches. Mol Biosyst 9:897–914PubMedCrossRefGoogle Scholar
  9. 9.
    Lomenick B et al (2009) Target identification using drug affinity responsive target stability (DARTS). Proc Natl Acad Sci U S A 106:21984–21989PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    Robinson TJ et al (2013) High-throughput screen identifies disulfiram as a potential therapeutic for triple-negative breast cancer cells: interaction with IQ motif-containing factors. Cell Cycle 12:3013–3024PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Chin RM et al (2014) The metabolite alpha-ketoglutarate extends lifespan by inhibiting ATP synthase and TOR. Nature. doi: 10.1038/nature13264 PubMedGoogle Scholar
  12. 12.
    Lomenick B et al (2011) Target identification using drug affinity responsive target stability (DARTS). Curr Protoc Chem Biol 3:163–180PubMedCentralPubMedGoogle Scholar
  13. 13.
    Tohda C et al (2012) Diosgenin is an exogenous activator of 1,25D(3)-MARRS/Pdia3/ERp57 and improves Alzheimer's disease pathologies in 5XFAD mice. Sci Rep 2:535PubMedCentralPubMedCrossRefGoogle Scholar
  14. 14.
    Sun W et al (2014) Chemical signatures and new drug targets for gametocytocidal drug development. Sci Rep 4:3743PubMedCentralPubMedGoogle Scholar
  15. 15.
    Aghajan M et al (2010) Chemical genetics screen for enhancers of rapamycin identifies a specific inhibitor of an SCF family E3 ubiquitin ligase. Nat Biotechnol 28:738–742PubMedCrossRefGoogle Scholar
  16. 16.
    Chen T et al (2011) Chemical genetics identify eIF2alpha kinase heme-regulated inhibitor as an anticancer target. Nat Chem Biol 7:610–616PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    Gao S et al (2012) The chemistry and biology of nakiterpiosin—C-nor-D-homosteroids. Synlett 16:2298–2310PubMedCentralPubMedGoogle Scholar
  18. 18.
    Xu S et al (2013) Stabilization of MDA-7/IL-24 for colon cancer therapy. Cancer Lett 335:421–430PubMedCrossRefGoogle Scholar
  19. 19.
    Lim M et al (2014) Ligand-independent and tissue-selective androgen receptor inhibition by pyrvinium. ACS Chem Biol 9:692–702PubMedCrossRefGoogle Scholar
  20. 20.
    Li H et al (2014) Drug design targeting protein-protein interactions (PPIs) using multiple ligand simultaneous docking (MLSD) and drug repositioning: discovery of raloxifene and bazedoxifene as novel inhibitors of IL-6/GP130 interface. J Med Chem 57:632–641PubMedCrossRefGoogle Scholar
  21. 21.
    Molina DM et al (2013) Monitoring drug target engagement in cells and tissues using the cellular thermal shift assay. Science 341:84–87CrossRefGoogle Scholar
  22. 22.
    Kragten E et al (1998) Glyceraldehyde-3-phosphate dehydrogenase, the putative target of the antiapoptotic compounds CGP 3466 and R-(-)-deprenyl. J Biol Chem 273:5821–5828PubMedCrossRefGoogle Scholar
  23. 23.
    Lundberg E et al (2010) Defining the transcriptome and proteome in three functionally different human cell lines. Mol Syst Biol 6:450PubMedCentralPubMedCrossRefGoogle Scholar
  24. 24.
    Geiger T et al (2012) Comparative proteomic analysis of eleven common cell lines reveals ubiquitous but varying expression of most proteins. Mol Cell Proteomics 11:M111 014050PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Geiger T et al (2013) Initial quantitative proteomic map of 28 mouse tissues using the SILAC mouse. Mol Cell Proteomics 12:1709–1722PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Molecular Biology InstituteUniversity of California Los AngelesLos AngelesUSA
  2. 2.Department of Molecular and Medical PharmacologyUniversity of California Los AngelesLos AngelesUSA
  3. 3.Department of Environmental Health SciencesUniversity of California Los AngelesLos AngelesUSA
  4. 4.Department of Radiation OncologyUniversity of California Los AngelesLos AngelesUSA
  5. 5.Department of PathologyUniversity of California Los AngelesLos AngelesUSA
  6. 6.Department of Biological ChemistryUniversity of California Los AngelesLos AngelesUSA

Personalised recommendations

Cite protocol

Buy options