A Digest of Protein Purification

  • Dermot Walls
  • Robert McGrath
  • Sinéad T. Loughran
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 681)

Abstract

The isolation of a given protein, free of all other biomolecules, is the primary objective of any protein purification scheme. Classical chromatographic procedures have been designed to exploit particular distinguishing features of individual target proteins, such as size, physico-chemical properties and binding affinity. Advances in molecular biology and bioinformatics have positively contributed at every level to the challenge of purifying individual proteins and more recently have led to the development of high-throughput proteomic platforms. Here, a summation of developments in the field of protein chromatography is given, coupled with a compilation of general resources and tools that are available to assist with protein purification processes.

Key words

Protein Purification Chromatography Proteome 

References

  1. 1.
    Sun, P.D., Foster, C.E., and Boyington, J.C. (2004) Overview of protein structural and functional folds. Curr. Protoc. Protein Sci. Chapter 17: Unit 17.1.Google Scholar
  2. 2.
    Kang, T.S. and Kini, R.M. (2009) Structural determinants of protein folding. Cell. Mol. Life Sci. 66, 2341–2361.PubMedCrossRefGoogle Scholar
  3. 3.
    Bartlett, A.I. and Radford, S.E. (2009) An expanding arsenal of experimental methods yields an explosion of insights into protein folding mechanisms. Nat. Struct. Mol. Biol. 16, 582–588.PubMedCrossRefGoogle Scholar
  4. 4.
    Strandberg, B. (2009) Building the ground for the first two protein structures: myoglobin and haemoglobin. J. Mol. Biol. 392, 2–10.PubMedCrossRefGoogle Scholar
  5. 5.
    Cohen, E.J., Strong, L.E., Hughes, W.L., Mulford, D.J., Ashworth, J.N., Melin, M., and Taylor, H.L. (1946) Preparation and properties of serum and plasma proteins. IV. A system for the separation into fractions of the proteins and lipoprotein components of biological tissues and fluids. J. Am. Chem. Soc. 68, 459–475.CrossRefGoogle Scholar
  6. 6.
    Katzen, F., Peterson, T.C., and Kudlicki, W. (2009) Membrane protein expression: no cells required. Trends Biotechnol. 27, 455–460.PubMedCrossRefGoogle Scholar
  7. 7.
    Gasteiger, E., Gattiker, A., Hoogland, C., Ivanyi, I., Appel, R.D., and Bairoch A. (2003) ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 31, 3784–3788.PubMedCrossRefGoogle Scholar
  8. 8.
    Craig, R., Cortens, J.P., and Beavis, R.C. (2004) Open source system for analyzing, validating, and storing protein identification data. J. Proteome Res. 3(6), 1234–1242.PubMedCrossRefGoogle Scholar
  9. 9.
    Rice, P., Longden, I., and Bleasby, A. (2000) EMBOSS: the European Molecular Biology Open Software Suite. Trends Genet. 16(6), 276–277.PubMedCrossRefGoogle Scholar
  10. 10.
    Fuhrmann, M., Hausherr, A., Ferbitz, L., Schödl, T., Heitzer, M., and Hegemann, P. (2004) Monitoring dynamic expression of nuclear genes in Chlamydomonas reinhardtii by using a synthetic luciferase reporter gene. Plant Mol. Biol. 55(6), 869–881.PubMedGoogle Scholar
  11. 11.
    Stothard, P. (2000) The Sequence Manipulation Suite: JavaScript programs for analyzing and formatting protein and DNA sequences. Biotechniques 28, 1102–1104.PubMedGoogle Scholar
  12. 12.
    Kessner, D., Chambers, M., Burke, R., Agus, D., and Mallick, P. (2008) ProteoWizard: Open source software for rapid proteomics tools development. Bioinformatics 24(21), 2534–2536.PubMedCrossRefGoogle Scholar
  13. 13.
    Bendtsen, J.D., Nielsen, H., von Heijne, G., and Brunak, S. (2004) Improved prediction of signal peptides: SignalP 3.0. Mol. Biol. 340, 783–795.CrossRefGoogle Scholar
  14. 14.
    Blom, N., Sicheritz-Ponten, T., Gupta, R., Gammeltoft, S., and Brunak, S. (2004) Prediction of post-translational glycosylation and phosphorylation of proteins from the amino acid sequence. Proteomics 4(6), 1633–1649.PubMedCrossRefGoogle Scholar
  15. 15.
    Gardy, J.L., Laird, M.R., Chen, F., Rey, S., Walsh, C.J., Ester, M., and Brinkman, F.S.L. (2005) PSORTb v.2.0: Expanded prediction of bacterial protein subcellular localization and insights gained from comparative ­proteome analysis. Bioinformatics 21(5), 617–623.PubMedCrossRefGoogle Scholar
  16. 16.
    Guda, C. (2006) pTARGET: a web server for predicting protein subcellular localization. Nucleic Acids Res. 34 (web server issue), W210–W213.PubMedCrossRefGoogle Scholar
  17. 17.
    Cserzo, M., Wallin, E., Simon, I., von Heijne, G., and Elofsson, A. (1997) Prediction of transmembrane alpha-helices in procariotic membrane proteins: the Dense Alignment Surface method. Prot. Eng. 10(6), 673–676.CrossRefGoogle Scholar
  18. 18.
    Hofmann, K. and Stoffel, W. (1993) TMbase – A database of membrane spanning proteins segments. Biol. Chem. Hoppe Seyler 374, 166.Google Scholar
  19. 19.
    Cole, C., Barber, J.D., and Barton, G.J. (2008) The Jpred 3 secondary structure prediction server. Nucleic Acids Res. 36 (web server issue), W197–W201.PubMedCrossRefGoogle Scholar
  20. 20.
    Diemand, A.V. and Scheib, H. (2004) MolTalk – a programming library for protein structures and structure analysis. BMC Bioinformatics, 5, 39.PubMedCrossRefGoogle Scholar
  21. 21.
    Sippl, M.J. and Wiederstein, M. (2008) A note on difficult structure alignment problems. Bioinformatics 24, 426–427.PubMedCrossRefGoogle Scholar
  22. 22.
    Kiefer, F., Arnold, K., Künzli, M., Bordoli, L., and Schwede, T. (2009). The SWISS-MODEL Repository and associated resources. Nucleic Acids Res. 37, D387–D392.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Dermot Walls
    • 1
  • Robert McGrath
    • 2
  • Sinéad T. Loughran
    • 1
  1. 1.School of Biotechnology and National Centre for Sensor ResearchDublin City UniversityDublinIreland
  2. 2.School of BiotechnologyDublin City UniversityDublinIreland

Personalised recommendations