Evidence map›Paper›PMID 41605870›Full record

ArticleJournal of the American Society for Mass Spectrometry2026

Quantitative Mapping of NHS Ester-Protein Reactivity Using Native Top-Down Mass Spectrometry.

Jack L Bennett, Olivia B Ramsay, Corinne A Lutomski, Carla Kirschbaum, Carol V Robinson

Abstract read
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 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

5 authors.

Jack L BennettKavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, Oxford OX1 3QU, U.K.ORCID 0009-0000-3505-2618
Olivia B RamsayKavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, Oxford OX1 3QU, U.K.ORCID 0009-0009-7284-2278
Corinne A LutomskiKavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, Oxford OX1 3QU, U.K.ORCID 0000-0001-7509-103X
Carla KirschbaumKavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, Oxford OX1 3QU, U.K.ORCID 0000-0003-3192-0785
Carol V RobinsonKavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, Oxford OX1 3QU, U.K.ORCID 0000-0001-7829-5505

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Covalent ligands are widely used to label, probe, and modulate proteins, but peptide-centric readouts obscure how modifications colocalize on intact proteoforms. This can limit insight into ligand mechanism, modification stoichiometry, and the architecture of multisite protein conjugates. We present a general native top-down mass spectrometry workflow that quantifies electrophile reactivity directly on intact proteins. Using NHS esters as a model electrophile class, we apply a deconvolution framework to infer differential reactivity at primary amines across promiscuous, multisite modification patterns. The approach preserves full modification connectivity, avoids sample-preparation artifacts associated with denaturation and digestion, and should extend to electrophiles with unknown reactivity. Overall, this framework provides a general platform for designing covalent therapeutics, bioconjugates, and activity-based probes with proteoform-level resolution.

Indexed as

Mass SpectrometryProteinsSuccinimidesEstersEstersProteinsSuccinimidescovalent modificationelectrophile reactivityintact proteinsnative top-down mass spectrometryNHS estersproteoform analysis

Identifiers

PMID41605870
PMCPMC12964535

What OpenQuestion holds

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Registered trials

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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.