Evidence map›Paper›PMID 41433248›Full record

ReviewJournal of medicinal chemistry2026

Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.

Lorenzo Tagliazucchi, Maria Paola Costi

Abstract readReview
In one paragraph

Review in Journal of medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
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

2 authors.

Lorenzo TagliazucchiDepartment of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy.
Maria Paola CostiDepartment of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi 103, 41125 Modena, Italy.ORCID 0000-0002-0443-5402

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mass spectrometry (MS)-based proteomics is a disruptive platform in drug discovery that offers an exhaustive view of the proteome's complexity. Focusing on bottom-up MS proteomics, this technology enables high-throughput analysis of protein expression, interactions, and modifications, far surpassing the capabilities of traditional single-protein methods. The MS proteomics toolbox is essential in both early- and late-stage development of new drugs. The techniques discussed here, such as unlabeled and labeled proteomics and chemoproteomic approaches (e.g., thermal proteome profiling and photoaffinity labeling), facilitate target binding site exploration and the identification of putative off-targets. By accelerating the identification of new druggable proteins and supporting early biomarker discovery, MS proteomics significantly accelerates the preclinical-to-clinical transition. Ongoing progress in data acquisition, new computational tools, and artificial intelligence further enhances the high-throughput properties of these approaches, marking a significant step toward personalized medicine.

Indexed as

Drug DiscoveryMass SpectrometryProteomicsAnimalsHumansProteomeProteome

Identifiers

PMID41433248
PMCPMC12794250

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.