Protocol | Published:

Thermodynamic analysis of protein-ligand binding interactions in complex biological mixtures using the stability of proteins from rates of oxidation

Nature Protocols volume 8, pages 148161 (2013) | Download Citation

Abstract

The detection and quantification of protein-ligand binding interactions is crucial in a number of different areas of biochemical research from fundamental studies of biological processes to drug discovery efforts. Described here is a protocol that can be used to identify the protein targets of biologically relevant ligands (e.g., drugs such as tamoxifen or cyclosporin A) in complex protein mixtures such as cell lysates. The protocol utilizes quantitative, bottom-up, shotgun proteomics technologies (isobaric mass tags for relative and absolute quantification, or iTRAQ) with a covalent labeling technique, termed stability of proteins from rates of oxidation (SPROX). In SPROX, the thermodynamic properties of proteins and protein-ligand complexes are assessed using the hydrogen peroxide–mediated oxidation of methionine residues as a function of the chemical denaturant (e.g., guanidine hydrochloride or urea) concentration. The proteome-wide SPROX experiments described here enable the ligand-binding properties of hundreds of proteins to be simultaneously assayed in the context of complex biological samples. The proteomic capabilities of the protocol render it amenable to the detection of both the on- and off-target effects of ligand binding. The protocol can be completed in 5 d.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    , & Thermodynamic analysis of protein stability and ligand binding using a chemical modification- and mass spectrometry-based strategy. Anal. Chem. 80, 4175–4185 (2008).

  2. 2.

    , & A quantitative, high-throughput screen for protein stability. Proc. Natl. Acad. Sci. USA 97, 8296–8301 (2000).

  3. 3.

    & Accuracy and precision of a new H/D exchange- and mass spectrometry-based technique for measuring the thermodynamic properties of protein-peptide complexes. Biochemistry 42, 4962–4670 (2003).

  4. 4.

    et al. Quantitative proteomics approach for identifying protein-drug interactions in complex mixtures using protein stability measurements. Proc. Natl. Acad. Sci. USA 107, 9078–9082 (2010).

  5. 5.

    , , , & Thermodynamic analysis of protein-ligand interactions in complex biological mixtures using a shotgun proteomics approach. J. Proteome Res. 10, 4948–4958 (2011).

  6. 6.

    & A novel genetic system to detect protein-protein interactions. Nature 340, 245–246 (1989).

  7. 7.

    et al. A generic protein purification method for protein complex characterization and proteome exploration. Nat. Biotechnol. 17, 1030–1032 (1999).

  8. 8.

    et al. Target identification using drug affinity responsive target stability (DARTS). Proc. Natl. Acad. Sci. USA 106, 21984–21989 (2009).

  9. 9.

    , & Energetics-based discovery of protein-ligand interactions on a proteomic scale. J. Mol. Biol. 408, 147–162 (2011).

  10. 10.

    , , & Stable isotope labeling strategy for protein-ligand binding analysis in multi-component protein mixtures. J. Am. Soc. Mass Spectrom. 22, 418–430 (2011).

  11. 11.

    et al. Mass spectrometry-based thermal shift assay for protein-ligand binding analysis. Anal. Chem. 82, 5573–5581 (2010).

  12. 12.

    The preparation of guanidine hydrochloride. Methods Enzymol. 26, 43–50 (1972).

  13. 13.

    Determination and analysis of urea and guanidine hydrochloride denaturation curves. Methods Enzymol. 131, 266–280 (1986).

  14. 14.

    & The reaction of ferrous horseradish peroxidase with hydrogen peroxide. J. Biol. Chem. 245, 2409–2413 (1970).

  15. 15.

    et al. Isolation and isotope labeling of cysteine- and methionine-containing tryptic peptides: application to the study of cell surface proteolysis. Mol. Cell Proteomics 2, 315–324 (2003).

Download references

Acknowledgements

This work was supported in part by US National Institutes of Health grant no. GM084174 (to M.C.F.) and in part by National Science Foundation (NSF) grant no. CHE-0848462 (to M.C.F.). The NSF grant, which was made possible with funds from the American Recovery and Reinvestment Act (ARRA), is jointly funded by the Analytical and Surface Chemistry Program in the Chemistry Division at NSF and by the Biomolecular Systems Cluster in the Division of Molecular and Cellular Biosciences at NSF. The mass spectrometer system used in this work was purchased with funds from National Institutes of Health grant no. S10RR027746 (to M.C.F.).

Author information

Author notes

    • Graham M West
    • , Patrick D DeArmond
    •  & Ying Xu

    Present addresses: The Scripps Research Institute, Jupiter, Florida, USA (G.M.W.), US Environmental Protection Agency, Las Vegas, Nevada (P.D.D.), and Clark University, Worcester, Massachusetts, USA (Y.X.).

Affiliations

  1. Department of Chemistry, Duke University, Durham, North Carolina, USA.

    • Erin C Strickland
    • , M Ariel Geer
    • , Graham M West
    • , Patrick D DeArmond
    • , Ying Xu
    •  & Michael C Fitzgerald
  2. Department of Biochemistry, Duke University Medical Center, Durham, North Carolina, USA.

    • Duc T Tran
    • , Jagat Adhikari
    •  & Michael C Fitzgerald

Authors

  1. Search for Erin C Strickland in:

  2. Search for M Ariel Geer in:

  3. Search for Duc T Tran in:

  4. Search for Jagat Adhikari in:

  5. Search for Graham M West in:

  6. Search for Patrick D DeArmond in:

  7. Search for Ying Xu in:

  8. Search for Michael C Fitzgerald in:

Contributions

G.M.W., P.D.D., Y.X., E.C.S., M.A.G., D.T.T. and J.A. contributed to the development and optimization of the described SPROX protocol. E.C.S. collected and analyzed the SPROX data highlighted in this manuscript. E.C.S., M.A.G., D.T.T., J.A. and M.C.F. drafted the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Michael C Fitzgerald.

Supplementary information

Excel files

  1. 1.

    Supplementary Data 1

    A sample data set on which Steps 36–43 were performed ("Sample_Data_Set.xlsx"). The data set is from the NAD binding study described in reference 5.

  2. 2.

    Supplementary Data 5

    The sample data set on which Steps 47–52 were performed ("Matched_NAD_Binding.xlsx")

Text files

  1. 1.

    Supplementary Data 2

    Runcompare input file used as a sample data set as described in Steps 44–46

  2. 2.

    Supplementary Data 3

    Runcompare input file used as a sample data set as described in Steps 44–46

  3. 3.

    Supplementary Data 4

    Output file generated from the sample data set as described in Steps 44–46

About this article

Publication history

Published

DOI

https://doi.org/10.1038/nprot.2012.146

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.