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Protein Identification Using Top-Down Spectra

2011; Elsevier BV; Volume: 11; Issue: 6 Linguagem: Inglês

10.1074/mcp.m111.008524

1535-9484

Xiaowen Liu, Yakov Sirotkin, Yufeng Shen, Gordon Anderson, Yihsuan S. Tsai, Ying S. Ting, David R. Goodlett, Richard Smith, Vineet Bafna, Pavel A. Pevzner,

Identification and Quantification in Food

In the last two years, because of advances in protein separation and mass spectrometry, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples and identifying hundreds and even thousands of proteins. However, computational tools for database search of top-down spectra against protein databases are still in their infancy. We describe MS-Align+, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications. We also propose a method for evaluating statistical significance of top-down protein identifications and further benchmark various software tools on two top-down data sets from Saccharomyces cerevisiae and Salmonella typhimurium. We demonstrate that MS-Align+ significantly increases the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the Salmonella typhimurium data set, MS-Align+ outperforms ProSightPC on the (more complex) Saccharomyces cerevisiae data set.