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Protein Identification by Peptide Mass Fingerprinting

  • Daniel C. Liebler
Chapter

Abstract

Peptide mass fingerprinting is a protein identification technique in which MS is used to measure the masses of proteolytic peptide fragments. The protein then is identified by matching the measured peptide masses to corresponding peptide masses from protein or nucleotide sequence databases. Peptide mass fingerprinting works well for analytical proteomics because it combines a conceptually simple approach with robust, high-throughput instrumentation (typically MALDI-TOF MS). As with other MS-based analytical proteomics techniques, the quality of the protein identifications made depend on the quality of both the MS data, the accuracy of the databases, and the power of the search algorithms and software used. In the remainder of this chapter, we will consider peptide mass fingerprinting in greater detail. We will describe how peptide mass measurements can be used to identify proteins and finally how algorithms and software can automate the identification process.

Keywords

Protein Identification Tryptic Peptide Peptide Mass Mass Tolerance Peptide Mass Fingerprinting 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Suggested Reading

  1. Fenyo, D. (2000) Identifying the proteome: software tools. Curr. Opin. Biotechnol. 11, 391–395.PubMedCrossRefGoogle Scholar
  2. Gras, R., Muller, M., Gasteiger, E., Gay, S., Binz, P. A., Bienvenut, W., et al. (1999) Improving protein identification from peptide mass fingerprinting through a parameterized multi-level scoring algorithm and an optimized peak detection. Electrophoresis 20, 3535–3550.PubMedCrossRefGoogle Scholar
  3. Jensen, O. N., Podtelejnikov, A. V., and Mann, M. (1997) Identification of the components of simple protein mixtures by high-accuracy peptide mass mapping and database searching. Anal. Chem. 69, 4741–4750.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • Daniel C. Liebler
    • 1
  1. 1.College of PharmacyThe University of ArizonaTucsonUSA

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