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Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...

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Related Experiment Video

Updated: Aug 30, 2025

Utilizing a Comprehensive Immunoprecipitation Enrichment System to Identify an Endogenous Post-translational Modification Profile for Target Proteins

Published on: January 8, 2018

Data-independent acquisition proteomics methods for analyzing post-translational modifications.

Yi Yang¹, Liang Qiao¹

¹Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China.

|August 29, 2022

Summary

This summary is machine-generated.

Data-independent acquisition mass spectrometry (DIA-MS) enables deep proteome coverage for identifying and quantifying protein post-translational modifications (PTMs). This review details DIA data processing for PTM detection, localization, and characterization, including deep learning applications.

Keywords:

LC-MS/MS data-independent acquisition glycosylation post-translational modifications site localization spectral library

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Last Updated: Aug 30, 2025

Utilizing a Comprehensive Immunoprecipitation Enrichment System to Identify an Endogenous Post-translational Modification Profile for Target Proteins

Published on: January 8, 2018

Quantification of Site-specific Protein Lysine Acetylation and Succinylation Stoichiometry Using Data-independent Acquisition Mass Spectrometry

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Published on: April 4, 2018

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

Published on: February 27, 2020

Area of Science:

Proteomics
Mass Spectrometry
Biochemistry

Background:

Protein post-translational modifications (PTMs) significantly expand proteome functional diversity.
High-throughput and accurate PTM identification and quantification are crucial in proteomics.
Data-independent acquisition (DIA) mass spectrometry (MS) offers deep proteome coverage and precise quantification.

Purpose of the Study:

To review DIA data processing methods for PTM analysis.
To cover PTM detection, site localization, and complex modification characterization (e.g., glycosylation).
To survey deep learning applications enhancing DIA-based PTM analysis.

Main Methods:

Overview of DIA data processing strategies for PTMs.
Discussion of methods for PTM detection and site localization.
Exploration of deep learning for spectral library generation, feature scoring, and error control in DIA-MS.

Main Results:

DIA-MS enables comprehensive analysis of protein PTMs.
Deep learning methods improve accuracy and efficiency in DIA-based PTM quantification.
Current limitations and future opportunities in DIA for PTMs are identified.

Conclusions:

DIA-MS is a powerful technology for in-depth PTM analysis.
Advancements in data analysis and MS instrumentation will further enhance PTM measurements.
Future directions focus on integrating novel methods for more accurate and extensive PTM characterization.