4.5 Article

FPTMS: Frequency-based approach to identify the peptide from the low-energy collision-induced dissociation tandem mass spectra

期刊

JOURNAL OF PROTEOMICS
卷 235, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.jprot.2021.104116

关键词

Proteomics; MS/MS; CID; Database search; Peptide identification; Sliding window correlation

资金

  1. Department of Electronics, Cochin University of Science and Technology

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A new method FPTMS was introduced to interpret tandem mass spectra, showing improved identification rate compared to existing search engines. The fragmentation behavior of peptides is complex and dependent on sequences, charge state, and residue content, with the inclusion of more features and adaptable scoring algorithms enhancing the efficiency of peptide identification algorithms.
The database search method is a widely accepted method to assign a peptide to the tandem mass spectra. In this study, a new flexible methodFPTMS is introduced to interpret the tandem mass spectra with the known peptide sequences in a protein database. Here the frequency of occurrence of fragment ion peaks extracted from the extensive spectral library is used to predict the theoretical tandem mass spectra of the peptides. The dot product scoring and windowed-xcorr scoring methods were implemented to score the experimental spectrum against the theoretical peptide spectra. Windowed-xcorr is introduced to tackle the mass errors and the cleavage position of the fragmentation process. The new method with windowed-xcorr shows an improved identification rate compared to the existing search engines Crux-Tide and X!Tandem at 1% False Discovery Rate (FDR) for the dataset considered in this study. Significance: Identifying or sequencing of the peptide from tandem mass spectra is an important application in mass spectrometry-based proteomics. Collision-induced dissociation (CID) fragmentation spectra have been widely used to develop a peptide identification algorithm using database search strategy. CID fragmentation behavior is a complex process and found to have dependency on the sequences of peptide, charge state, and residue content. The inclusion of more features of peptide fragmentation behavior and adaptable scoring algorithm improves the efficiency of the peptide identification algorithm.

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