An algorithm for peptide de novo sequencing from a group of SILAC labeled MS/MS spectra

Shotgun proteomics coupled with high-performance liquid chromatography and mass spectrometry has been instrumental in identifying proteins in complex mixtures. Effective computational approaches are required to automate the spectra interpretation process to handle the vast amount of data collected i...

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Veröffentlicht in:Journal of bioinformatics and computational biology Jg. 23; H. 3; S. 2550007
Hauptverfasser: Han, Fang, Zhang, Kaizhong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Singapore 01.06.2025
Schlagworte:
Algorithms
Amino Acid Sequence
Chromatography, Liquid
Humans
Isotope Labeling - methods
Peptides - chemistry
Proteomics - methods
Sequence Analysis, Protein - methods
Tandem Mass Spectrometry - methods
mass spectrometry
SILAC
multiple MS/MS spectra
Bioinformatics
computational proteomics
de novo sequencing
ISSN:1757-6334, 1757-6334
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Zusammenfassung:Shotgun proteomics coupled with high-performance liquid chromatography and mass spectrometry has been instrumental in identifying proteins in complex mixtures. Effective computational approaches are required to automate the spectra interpretation process to handle the vast amount of data collected in a single Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) run. De novo sequencing from MS/MS has emerged as a vital technology for peptide sequencing in proteomics. To enhance the accuracy and practicality of de novo sequencing, previous algorithms have utilized multiple spectra to identify peptide sequences. Here, our study focuses on de novo sequencing of multiple tandem mass spectra of peptides with stable isotope labeling with amino acids in cell culture (SILAC) by incorporating different isotope-labeled amino acids into newly synthesized proteins. Multiple MS/MS spectra for the same peptide sequence are produced by the spectrometer after the SILAC samples undergo processing by LC-MS/MS shotgun proteomics. Taking into consideration the factors such as retention time and precursor ion mass, we aim to identify the peptide sequence with specific SILAC modifications and their locations. To do so, we propose de novo sequencing algorithms to compute the potential candidate peptide sequence by using similarity scores, followed by refinement algorithms to evaluate them. We also use real experimental data to test the algorithms.
Bibliographie:ObjectType-Article-1
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content type line 23
ISSN:1757-6334
1757-6334
DOI:10.1142/S0219720025500076