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Comparison of search engine contributions in protein mass fingerprinting for protein identification

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Abstract

Peptide mass fingerprinting (PMF) is a valuable method for rapid and high-throughput protein identification using the proteomics approach. Automated search engines, such as Ms-Fit, Mascot, ProFound, and Peptldent, have facilitated protein identification through PMF. The potential to obtain a true MS protein identification result depends on the choice of algorithm as well as experimental factors that influence the information content in MS data. When mass spectral data are incomplete and/or have low mass accuracy, the “number of matches” approach may be inadequate for a useful identification. Several studies have evaluated factors influencing the quality of mass spectrometry (MS) experiments. Missed cleavages, posttranslational modifications of peptides and contaminants (e.g., keratin) are important factors that can affect the results of MS analyses by influencing the identification process as well as the quality of the MS spectra. We compared search engines frequently used to identify proteins fromHomo sapiens andHalobacterium salinarum by evaluating factors, including data-based and mass tolerance to develop an improved search engine for PMF. This study may provide information to help develop a more effective algorithm for protein identification in each species through PMF.

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Author notes

  1. Won-A Joo

    Present address: Wistar Institute, Philadelphia, USA

Authors and Affiliations

  1. School of Life Sciences and Biotechnology, Korea University, 136-701, Seoul, Korea

    Won-A Joo, Hyun-Jung Kim & Chan-Wha Kim

  2. Department of Statistics, Korea University, 136-701, Seoul, Korea

    Jeong-Bok Lee & Jae-Won Lee

  3. Department of Premedicine, Eulji University, 301-832, Daejeon, Korea

    Mira Park

Authors
  1. Won-A Joo
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  2. Jeong-Bok Lee
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  3. Mira Park
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  4. Jae-Won Lee
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  5. Hyun-Jung Kim
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  6. Chan-Wha Kim
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Corresponding author

Correspondence to Chan-Wha Kim.

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Joo, WA., Lee, JB., Park, M. et al. Comparison of search engine contributions in protein mass fingerprinting for protein identification. Biotechnol. Bioprocess Eng. 12, 125–130 (2007). https://doi.org/10.1007/BF03028637

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  • DOI: https://doi.org/10.1007/BF03028637

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