Evidence map›Paper›PMID 42213770›Full record

ReviewSTAR protocols2026

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

Yiying Zhu

Abstract readReview
In one paragraph

Review in STAR protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Yiying ZhuDepartment of Chemistry, Tsinghua University, Beijing 100084, China. Electronic address: yiying_zhu@mail.tsinghua.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Liquid Chromatography-Mass SpectrometryProtein Processing, Post-TranslationalProteinsProteomicsTandem Mass SpectrometryProteinsChemistryMass SpectrometryProteomics

Identifiers

PMID42213770
PMCPMC13241734

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.