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Record W4413347132 · doi:10.1021/acs.jproteome.5c00341

Metabolite Functions Revealed by Mass Spectrometry-Based Target Engagement Proteomics Approaches

2025· review· en· W4413347132 on OpenAlexafffund
Nisha A. Owens, Tayah B. Sommer, Brenna G. Ing, Mukhayyo Sultonova, J. Patrick Murphy

Bibliographic record

VenueJournal of Proteome Research · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsDalhousie UniversityUniversity of Prince Edward Island
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Cancer Society
KeywordsProteomicsMass spectrometryMetaboliteMetabolomicsChemistryMetabolite profilingComputational biologyChromatographyBiologyBiochemistry

Abstract

fetched live from OpenAlex

In addition to their roles in energetics and biosynthesis, endogenous metabolites have functional roles performed in part through protein interactions that result in allosteric regulation, transcriptional regulation, and post-translational modifications. Novel bioactive roles for metabolites continue to emerge in cancer progression, immune response, and host-pathogen interactions. Defining metabolite-protein interactions will further reveal bioactive metabolite downstream effects and help to characterize the intersection between the metabolome and the proteome. Here, we summarize recently revealed secondary functions for metabolites that have been uncovered by mass spectrometry-based approaches for small molecule target engagement. We propose that further developments and application of these approaches will greatly advance our understanding of metabolite functions and may facilitate large-scale metabolome-proteome interaction networks that harbor new targets for diseases such as cancer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.138
GPT teacher head0.395
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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