Peptide sequence tag generation for tandem mass spectra containing post-translational modifications

2012 ◽  
Vol 5 (3/4) ◽  
pp. 325
Author(s):  
Hui Li ◽  
Chunmei Liu
Keyword(s):  
Mass Spectra ◽  
Peptide Sequence ◽  
Tandem Mass ◽  
Post Translational Modifications ◽  
Tandem Mass Spectra

scholarly journals Understanding the limit of open search in the identification of peptides with post-translational modifications — A simulation-based study

2018 ◽  
Author(s):  
Jiaan Dai ◽  
Fengchao Yu ◽  
Ning Li ◽  
Weichuan Yu
Keyword(s):  
Analytical Model ◽  
Mass Spectra ◽  
Mass Spectrometry Data ◽  
Supplementary Information ◽  
Necessary Condition ◽  
Tandem Mass ◽  
Search Methods ◽  
Post Translational Modifications ◽  
Tandem Mass Spectra ◽  
The Relationship

AbstractMotivationAnalyzing tandem mass spectrometry data to recognize peptides in a sample is the fundamental task in computational proteomics. Traditional peptide identification algorithms perform well when identifying unmodified peptides. However, when peptides have post-translational modifications (PTMs), these methods cannot provide satisfactory results. Recently, Chick et al., 2015 and Yu et al., 2016 proposed the spectrum-based and tag-based open search methods, respectively, to identify peptides with PTMs. While the performance of these two methods is promising, the identification results vary greatly with respect to the quality of tandem mass spectra and the number of PTMs in peptides. This motivates us to systematically study the relationship between the performance of open search methods and quality parameters of tandem mass spectrum data, as well as the number of PTMs in peptides.ResultsThrough large-scale simulations, we obtain the performance trend when simulated tandem mass spectra are of different quality. We propose an analytical model to describe the relationship between the probability of obtaining correct identifications and the spectrum quality as well as the number of PTMs. Based on the analytical model, we can quantitatively describe the necessary condition to effectively apply open search methods.AvailabilitySource codes of the simulation are available at http://bioinformatics.ust.hk/[email protected] or [email protected] informationSupplementary data are available at Bioinformatics online.

scholarly journals Protocol for analysis of glycoproteomics LC-MS data using GlycReSoft

2020 ◽  
Author(s):  
Joshua A. Klein ◽  
Joseph Zaia
Keyword(s):  
Mass Spectra ◽  
Software Tool ◽  
Database Search ◽  
Peptide Sequence ◽  
Data Sets ◽  
Tandem Mass ◽  
Exact Mass ◽  
Tandem Mass Spectra ◽  
Search Results ◽  
Data Files

Summary/AbstractThe GlycReSoft software tool allows users to process glycoproteomics LC-MS data sets. The tool accepts proteomics database search results or a user-defined list of proteins in the sample. GlycReSoft processes LC-MS data to yield deconvoluted exact mass values. The user has the option to import a list of theoretical glycans from an external database, a curated glycan list, or a measured glycome. The tool assembles a list of theoretical glycopeptides from the lists of theoretical glycans and proteins, respectively. The program then scores the tandem mass spectra in the LC-MS data files and provides graphical views of the identified glycopeptides for each protein in the sample, and the set of glycoforms identified for each peptide sequence.

Unrestrictive protein modification localization and quality control for open search of mass spectra

2018 ◽  
Author(s):  
Zhiwu An ◽  
Fuzhou Gong ◽  
Yan Fu
Keyword(s):  
Mass Spectrometry ◽  
Quality Control ◽  
Tandem Mass Spectrometry ◽  
Mass Spectra ◽  
Protein Modification ◽  
Software Tool ◽  
Tandem Mass ◽  
Simulation Data ◽  
Post Translational Modifications

We have developed PTMiner, a first software tool for automated, confident filtering, localization and annotation of protein post-translational modifications identified by open (mass-tolerant) search of large tandem mass spectrometry datasets. The performance of the software was validated on carefully designed simulation data. <br>

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