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Peptide Identification Using Tandem Mass Spectrometry

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Predicting peptide retention times for proteomics.

Oleg V Krokhin¹, Vic Spicer

¹Department of Internal Medicine, University of Manitoba, Winnipeg, Canada.

Current Protocols in Bioinformatics

|September 14, 2010

Summary

Predicting peptide retention times using the Sequence Specific Retention Calculator (SSRCalc) web tool enhances proteomic analyses. This method improves protein identification by accurately forecasting peptide behavior during liquid chromatography-mass spectrometry.

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Area of Science:

Proteomics
Analytical Chemistry
Bioinformatics

Background:

Modern bottom-up proteomics heavily relies on liquid chromatography-mass spectrometry (LC-MS) for peptide analysis.
Peptide retention time data from LC-MS is crucial for improving protein identification and characterization.
Accurate prediction of peptide retention times is essential for optimizing chromatographic separation.

Purpose of the Study:

To introduce the Sequence Specific Retention Calculator (SSRCalc), a web-based tool for predicting peptide retention times.
To demonstrate the application of SSRCalc in proteomic workflows.
To enhance the accuracy of peptide identification and characterization in LC-MS analyses.

Main Methods:

Development of a web-based tool, SSRCalc, for peptide retention time prediction.
Utilizing Sequence Specific Retention Calculator (SSRCalc) for predicting peptide retention based on sequence and properties.
Applying SSRCalc to popular reversed-phase high-performance liquid chromatography (RP-HPLC) conditions used in proteomics.

Main Results:

SSRCalc provides accurate peptide retention time predictions for common RP-HPLC conditions.
The tool covers the separation selectivity relevant to standard proteomics protocols.
SSRCalc facilitates improved protein identification by leveraging predicted retention data.

Conclusions:

The Sequence Specific Retention Calculator (SSRCalc) is a valuable tool for proteomic research.
Accurate retention time prediction significantly aids in peptide and protein identification.
SSRCalc streamlines proteomic data analysis by integrating sequence-specific predictions.