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Peptide Identification Using Tandem Mass Spectrometry

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

Tandem Mass Spectrometry

Tandem Mass Spectrometry

Tandem mass spectrometry is a technique that uses multiple mass analyzers in series to obtain a higher selectivity and reduce chemical noise during analyte detection. Instruments with multiple analyzers separated by an interaction cell enable secondary fragmentation and selected study of the fragment ions.Secondary fragmentations occur in the interaction cell and can be induced by various factors. Fragmentation induced by collision with inert gases, such as N2, Ar, He, etc., is called...

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Related Experiment Video

Updated: May 7, 2026

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

Published on: October 20, 2016

MS2PIP: a tool for MS/MS peak intensity prediction.

Sven Degroeve¹, Lennart Martens

¹Department of Medical Protein Research, VIB, Ghent 9000, Belgium and Department of Biochemistry, Ghent University, Ghent 9000, Belgium.

Bioinformatics (Oxford, England)

|October 1, 2013

Summary

MS(2)PIP is a new tool that predicts peptide fragmentation patterns in mass spectrometry. It outperforms existing methods, improving high-throughput proteomics research.

Area of Science:

Proteomics
Mass Spectrometry
Computational Biology

Background:

Tandem mass spectrometry (MS2) is crucial for identifying peptides by analyzing their fragmentation patterns.
Understanding peptide fragmentation is vital for sensitive, high-throughput proteomics.
Predicting MS2 spectra aids in matching observed signals to specific chemical entities.

Purpose of the Study:

To develop a novel computational tool for predicting peptide MS2 spectra.
To improve the accuracy of peptide identification in mass spectrometry-based proteomics.

Main Methods:

Developed MS2PIP, a tool utilizing a random forest regression algorithm.
Trained the model on a large dataset of confident peptide-to-spectrum matches.
Employed collision-induced dissociation (CID) fragmentation data.

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Published on: March 24, 2016

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Last Updated: May 7, 2026

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

Published on: October 20, 2016

Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization (IR-MALDESI)

Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization (IR-MALDESI)

Published on: March 24, 2016

Main Results:

MS2PIP accurately predicts the intensity of key fragment ion peaks from peptide sequences.
The tool demonstrates significantly better correlation with observed fragment-ion intensities compared to PeptideART.
Evaluated performance on multiple independent datasets.

Conclusions:

MS2PIP offers a significant advancement in predicting peptide fragmentation spectra.
The tool enhances the accuracy and efficiency of high-throughput proteomics research.
MS2PIP code is publicly available for training and prediction.