A decision-driven framework for the mass spectrometry analysis of previously uncharacterized protein modifications

Identification of unknown protein modifications remains challenging when the modification chemistry or site is not defined in advance. Conventional workflows often rely on predefined modification lists or enrichment strategies that assume prior knowledge of modification type and may therefore bias discovery toward annotated post-translational modifications (PTMs). This primer outlines a decision-driven analytical framework for investigating previously uncharacterized modifications using bottom-up (liquid chromatography-tandem mass spectrometry) LC-MS/MS that emphasizes chemistry-informed hypothesis generation, iterative refinement of candidate modification search space, integration of experimental controls, and targeted data interpretation. Rather than presenting a single prescriptive workflow, the guide highlights key decision points in experimental design, acquisition strategy, and database search configuration that influence confident identification and residue-level localization. The framework is broadly applicable to drug-induced covalent adducts, chemically introduced modifications, as well as endogenous modifications arising across diverse experimental and biological contexts.

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Publication Details

Journal
STAR Protocols
Published
2026-05-29
DOI
https://doi.org/10.1016/j.xpro.2026.104567
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
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article

A decision-driven framework for the mass spectrometry analysis of previously uncharacterized protein modifications

Yiying Zhu
STAR Protocols
Advanced Proteomics Techniques and Applications
article

A decision-driven framework for the mass spectrometry analysis of previously uncharacterized protein modifications

Yiying Zhu
article en

Abstract

Identification of unknown protein modifications remains challenging when the modification chemistry or site is not defined in advance. Conventional workflows often rely on predefined modification lists or enrichment strategies that assume prior knowledge of modification type and may therefore bias discovery toward annotated post-translational modifications (PTMs). This primer outlines a decision-driven analytical framework for investigating previously uncharacterized modifications using bottom-up (liquid chromatography-tandem mass spectrometry) LC-MS/MS that emphasizes chemistry-informed hypothesis generation, iterative refinement of candidate modification search space, integration of experimental controls, and targeted data interpretation. Rather than presenting a single prescriptive workflow, the guide highlights key decision points in experimental design, acquisition strategy, and database search configuration that influence confident identification and residue-level localization. The framework is broadly applicable to drug-induced covalent adducts, chemically introduced modifications, as well as endogenous modifications arising across diverse experimental and biological contexts.

STAR ProtocolsVol. 7(2)
Tsinghua University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 11%
Advanced Proteomics Techniques and Applications
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