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Proteome-derived, database-searchable peptide libraries for identifying protease cleavage sites

Nature Biotechnology volume 26, pages 685–694 (2008)Cite this article

Abstract

We introduce human proteome–derived, database-searchable peptide libraries for characterizing sequence-specific protein interactions. To identify endoprotease cleavage sites, we used peptides in such libraries with protected primary amines to simultaneously determine sequence preferences on the N-terminal (nonprime P) and C-terminal (prime P′) sides of the scissile bond. Prime-side cleavage products were tagged with biotin, isolated and identified by tandem mass spectrometry, and the corresponding nonprime-side sequences were derived from human proteome databases using bioinformatics. Identification of hundreds to over 1,000 individual cleaved peptides allows the consensus protease cleavage site and subsite cooperativity to be readily determined from P6 to P6′. For the highly specific GluC protease, >95% of the 558 cleavage sites identified displayed the canonical selectivity. For the broad-specificity matrix metalloproteinase 2, >1,200 peptidic cleavage sites were identified. Profiling of HIV protease 1, caspase 3, caspase 7, cathepsins K and G, elastase and thrombin showed that this approach is broadly applicable to all mechanistic classes of endoproteases.

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Figure 1: PICS peptide library generation and cleavage site screen.
Figure 2: GluC cleavage sites of a tryptic PICS library.
Figure 3: MMP-2 cleavage sites in peptide libraries.
Figure 4: Amino-acid occurrences in P4–P4′ for MMP-2 cleavage sites in tryptic and GluC peptide libraries.
Figure 5: MMP-2 specificity profile.
Figure 6: Application of PICS to serine, aspartic and cysteine proteases.

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References

  1. Diamond, S.L. Methods for mapping protease specificity. Curr. Opin. Chem. Biol. 11, 4651 (2007).

    Article  CAS  Google Scholar 

  2. Schilling, O. & Overall, C.M. Proteomic discovery of protease substrates. Curr. Opin. Chem. Biol. 11, 36–45 (2007).

    Article  CAS  PubMed  Google Scholar 

  3. Overall, C.M. & Kleifeld, O. Validating matrix metalloproteinases as drug targets and antitargets for cancer therapy. Nat. Rev. Cancer 6, 227–239 (2006).

    Article  CAS  PubMed  Google Scholar 

  4. Puente, X.S., Sanchez, L.M., Overall, C.M. & LópezOtín, C. Human and mouse proteases: a comparative genomic approach. Nat. Rev. Genet. 4, 544–558 (2003).

    Article  CAS  PubMed  Google Scholar 

  5. Rawlings, N.D., Morton, F.R., Kok, C.Y., Kong, J. & Barrett, A.J. MEROPS: the peptidase database. Nucleic Acids Res. 36, D320–325 (2008).

    Article  CAS  PubMed  Google Scholar 

  6. Schechter, I. & Berger, A. On the size of the active site in proteases. I. Papain. Biochem. Biophys. Res. Commun. 27, 157–162 (1967).

    Article  CAS  PubMed  Google Scholar 

  7. Schechter, I. Mapping of the active site of proteases in the 1960s and rational design of inhibitors/drugs in the 1990s. Curr. Protein Pept. Sci. 6, 501–512 (2005).

    Article  CAS  PubMed  Google Scholar 

  8. Turk, B. Targeting proteases: successes, failures and future prospects. Nat. Rev. Drug Discov. 5, 785–799 (2006).

    Article  CAS  PubMed  Google Scholar 

  9. Matthews, D.J. & Wells, J.A. Substrate phage: selection of protease substrates by monovalent phage display. Science 260, 1113–1117 (1993).

    Article  CAS  PubMed  Google Scholar 

  10. Boulware, K.T. & Daugherty, P.S. Protease specificity determination by using cellular libraries of peptide substrates (CLiPS). Proc. Natl. Acad. Sci. USA 103, 7583–7588 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Chen, E.I. et al. A unique substrate recognition profile for matrix metalloproteinase-2. J. Biol. Chem. 277, 4485–4491 (2001).

    Article  CAS  PubMed  Google Scholar 

  12. Kerr, F.K. et al. Elucidation of the substrate specificity of the C1s protease of the classical complement pathway. J. Biol. Chem. 280, 39510–39514 (2005).

    Article  CAS  PubMed  Google Scholar 

  13. Rano, T.A. et al. A combinatorial approach for determining protease specificities: application to interleukin-1β converting enzyme (ICE). Chem. Biol. 4, 149–155 (1997).

    Article  CAS  PubMed  Google Scholar 

  14. Harris, J.L. et al. Rapid and general profiling of protease specificity by using combinatorial fluorogenic substrate libraries. Proc. Natl. Acad. Sci. USA 97, 7754–7759 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Harris, J. et al. Activity profile of dust mite allergen extract using substrate libraries and functional proteomic microarrays. Chem. Biol. 11, 1361–1372 (2004).

    Article  CAS  PubMed  Google Scholar 

  16. Salisbury, C.M., Maly, D.J. & Ellman, J.A. Peptide microarrays for the determination of protease substrate specificity. J. Am. Chem. Soc. 124, 14868–14870 (2002).

    Article  CAS  PubMed  Google Scholar 

  17. Gosalia, D.N., Salisbury, C.M., Ellman, J.A. & Diamond, S.L. High throughput substrate specificity profiling of serine and cysteine proteases using solution-phase fluorogenic peptide microarrays. Mol. Cell. Proteomics 4, 626–636 (2005).

    Article  CAS  PubMed  Google Scholar 

  18. Winssinger, N. et al. PNA-encoded protease substrate microarrays. Chem. Biol. 11, 1351–1360 (2004).

    Article  CAS  PubMed  Google Scholar 

  19. Turk, B.E., Huang, L.L., Piro, E.T. & Cantley, L.C. Determination of protease cleavage site motifs using mixture-based oriented peptide libraries. Nat. Biotechnol. 19, 661–667 (2001).

    Article  CAS  PubMed  Google Scholar 

  20. Gorodkin, J., Heyer, L.J., Brunak, S. & Stormo, G.D. Displaying the information contents of structural RNA alignments: the structure logos. Comput. Appl. Biosci. 13, 583–586 (1997).

    CAS  PubMed  Google Scholar 

  21. Schneider, T.D. & Stephens, R.M. Sequence logos: a new way to display consensus sequences. Nucleic Acids Res. 18, 6097–6100 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Kersey, P.J. et al. The International Protein Index: an integrated database for proteomics experiments. Proteomics 4, 1985–1988 (2004).

    Article  CAS  PubMed  Google Scholar 

  23. Drapeau, G.R., Boily, Y. & Houmard, J. Purification and properties of an extracellular protease of Staphylococcus aureus. J. Biol. Chem. 247, 6720–6726 (1972).

    CAS  PubMed  Google Scholar 

  24. Netzel-Arnett, S. et al. Comparative sequence specificities of human 72 and 92-kDa gelatinases (type IV collagenases) and PUMP (matrilysin). Biochemistry 32, 6427–6432 (1993).

    Article  CAS  PubMed  Google Scholar 

  25. Nagase, H. & Fields, G.B. Human matrix metalloproteinase specificity studies using collagen sequence-based synthetic peptides. Biopolymers 40, 399–416 (1996).

    Article  CAS  PubMed  Google Scholar 

  26. Gomis-Ruth, F.X. Structural aspects of the metzincin clan of metalloendopeptidases. Mol. Biotechnol. 24, 157–202 (2003).

    Article  CAS  PubMed  Google Scholar 

  27. Maskos, K. Crystal structures of MMPs in complex with physiological and pharmacological inhibitors. Biochimie 87, 249–263 (2005).

    Article  CAS  PubMed  Google Scholar 

  28. Thornberry, N.A. et al. A combinatorial approach defines specificities of members of the caspase family and granzyme B. Functional relationships established for key mediators of apoptosis. J. Biol. Chem. 272, 17907–17911 (1997).

    Article  CAS  PubMed  Google Scholar 

  29. Stephens, A.W., Siddiqui, A. & Hirs, C.H. Site-directed mutagenesis of the reactive center (serine 394) of antithrombin III. J. Biol. Chem. 263, 15849–15852 (1988).

    CAS  PubMed  Google Scholar 

  30. Lecaille, F., Bromme, D. & Lalmanach, G. Biochemical properties and regulation of cathepsin K activity. Biochimie 90, 208–226 (2008).

    Article  CAS  PubMed  Google Scholar 

  31. Fosang, A.J. et al. The interglobular domain of cartilage aggrecan is cleaved by PUMP, gelatinases, and cathepsin B. J. Biol. Chem. 267, 19470–19474 (1992).

    CAS  PubMed  Google Scholar 

  32. Stetler-Stevenson, W.G., Krutzsch, H.C., Wacher, M.P., Margulies, I.M. & Liotta, L.A. The activation of human type IV collagenase proenzyme. Sequence identification of the major conversion product following organomercurial activation. J. Biol. Chem. 264, 1353–1356 (1989).

    CAS  PubMed  Google Scholar 

  33. Van Damme, P. et al. Caspase–specific and nonspecific in vivo protein processing during Fas-induced apoptosis. Nat. Methods 2, 771–777 (2005).

    Article  CAS  PubMed  Google Scholar 

  34. Perkins, D.N., Pappin, D.J., Creasy, D.M. & Cottrell, J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551–3567 (1999).

    Article  CAS  PubMed  Google Scholar 

  35. López–Otín, C. & Overall, C.M. Protease degradomics: a new challenge for proteomics. Nat. Rev. Mol. Cell Biol. 3, 509–519 (2002).

    Article  CAS  PubMed  Google Scholar 

  36. Tam, E.M., Morrison, C.J., Wu, Y.I., Stack, M.S. & Overall, C.M. Membrane protease proteomics: isotope-coded affinity tag MS identification of undescribed MT1-matrix metalloproteinase substrates. Proc. Natl. Acad. Sci. USA 101, 6917–6922 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Dean, R.A. & Overall, C.M. Proteomics discovery of metalloproteinase substrates in the cellular context by iTRAQ™ labeling reveals a diverse MMP–2 substrate degradome. Mol. Cell. Proteomics 6, 611–623 (2007).

    Article  CAS  PubMed  Google Scholar 

  38. McDonald, L., Robertson, D.H., Hurst, J.L. & Beynon, R.J. Positional proteomics: selective recovery and analysis of N-terminal proteolytic peptides. Nat. Methods 2, 955–957 (2005).

    Article  CAS  PubMed  Google Scholar 

  39. Enoksson, M. et al. Identification of proteolytic cleavage sites by quantitative proteomics. J. Proteome Res. 6, 2850–2858 (2007).

    Article  CAS  PubMed  Google Scholar 

  40. Overall, C.M., McQuibban, G.A. & Clark-Lewis, I. Discovery of chemokine substrates for matrix metalloproteinases by exosite scanning: a new tool for degradomics. Biol. Chem. 383, 1059–1066 (2002).

    Article  CAS  PubMed  Google Scholar 

  41. McQuibban, G.A. et al. Inflammation dampened by gelatinase A cleavage of monocyte chemoattractant protein-3. Science 289, 1202–1206 (2000).

    Article  CAS  PubMed  Google Scholar 

  42. Boyd, S.E., Pike, R.N., Rudy, G.B., Whisstock, J.C. & Garcia de la Banda, M. PoPS: a computational tool for modeling and predicting protease specificity. J. Bioinform. Comput. Biol. 3, 551–585 (2005).

    Article  CAS  PubMed  Google Scholar 

  43. Dean, R.A. et al. Identification of candidate angiogenic inhibitors processed by matrix metalloproteinase 2 (MMP-2) in cell-based proteomic screens: disruption of vascular endothelial growth factor (VEGF)/heparin affin regulatory peptide (pleiotrophin) and VEGF/connective tissue growth factor angiogenic inhibitory complexes by MMP2 proteolysis. Mol. Cell. Biol. 27, 8454–8465 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Bigg, H.F. et al. Tissue inhibitor of metalloproteinases-4 inhibits but does not support the activation of gelatinase A via efficient inhibition of membrane type 1-matrix metalloproteinase. Cancer Res. 61, 3610–3618 (2001).

    CAS  PubMed  Google Scholar 

  45. Stricklin, G.P., Jeffrey, J.J., Roswit, W.T. & Eisen, A.Z. Human skin fibroblast procollagenase: mechanisms of activation by organomercurials and trypsin. Biochemistry 22, 61–68 (1983).

    Article  CAS  PubMed  Google Scholar 

  46. Keller, A., Nesvizhskii, A.I., Kolker, E. & Aebersold, R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 74, 5383–5392 (2002).

    Article  CAS  PubMed  Google Scholar 

  47. Elias, J.E., Haas, W., Faherty, B.K. & Gygi, S.P. Comparative evaluation of mass spectrometry platforms used in largescale proteomics investigations. Nat. Methods 2, 667–675 (2005).

    Article  CAS  PubMed  Google Scholar 

  48. Stephan, C. et al. Automated reprocessing pipeline for searching heterogeneous mass spectrometric data of the HUPO Brain Proteome Project pilot phase. Proteomics 6, 5015–5029 (2006).

    Article  CAS  PubMed  Google Scholar 

  49. Martens, L. et al. PRIDE: the proteomics identifications database. Proteomics 5, 3537–3545 (2005).

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors thank S. Perry, S. He and W. Chen (UBC) for mass spectrometer operation, U. auf dem Keller (UBC) for scientific discussion, S. Boyd (Monash University, Melbourne, Australia) for assistance in building the MMP-2 PoPS model and L. Martens (European Bioinformatics Institute) for assistance with data submission to PRIDE. O.S. was supported by the Deutsche Forschungsgemeinschaft and the Michael Smith Foundation for Health Research. C.M.O. is supported by a Canada Research Chair in Metalloproteinase Proteomics and Systems Biology with research grants from the Canadian Institutes of Health Research, the National Cancer Institute of Canada (with funds raised by the Canadian Cancer Association), and the Canadian Breast Cancer Research Alliance Special Program Grant on Metastasis as well as with a center grant from the Michael Smith Research Foundation.

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  1. Oliver Schilling

    Present address: Present address: Institute of Molecular Medicine and Cell Research, University of Freiburg, Stefan-Meier-Strasse 17, D-79104 Freiburg, Germany.,

Authors and Affiliations

  1. Departments of Oral Biological and Medical Sciences, The UBC Centre for Blood Research, and Biochemistry and Molecular Biology, 4.401 Life Sciences Institute, 2350 Health Sciences Mall, University of British Columbia, Vancouver, V6T 1Z3, British Columbia, Canada

    Oliver Schilling & Christopher M Overall

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Contributions

O.S. designed and implemented the chemistry in the workflow, performed all analyses, wrote the Perl scripts and performed the bioinformatics and wrote and edited the paper. C.M.O. conceived, designed and oversaw the development of PICS, performed proof of concept experiments, wrote and edited the paper and provided financial support for the project.

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Correspondence to Christopher M Overall.

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Schilling, O., Overall, C. Proteome-derived, database-searchable peptide libraries for identifying protease cleavage sites. Nat Biotechnol 26, 685–694 (2008). https://doi.org/10.1038/nbt1408

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