Evidence map›Paper›PMID 38022804›Full record

ArticleAdvanced pharmaceutical bulletin2023

Mapping the Evolution of Activity-Based Protein Profiling: A Bibliometric Review.

Exequiel Oscar Jesus Porta

Abstract readEditorial
In one paragraph

Article in Advanced pharmaceutical bulletin, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Activity-based protein profiling: A graphical review.Current research in pharmacology and drug discovery · 2023
    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

1 author.

Exequiel Oscar Jesus PortaDepartment of Chemistry, Durham University, Durham, DH1 3LE, United Kingdom.ORCID https://orcid.org/0000-0002-7463-1468

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Activity-based protein profiling (ABPP) is a chemoproteomic approach that employs small-molecule probes to directly evaluate protein functionality within complex proteomes. This technology has proven to be a potent strategy for mapping ligandable sites in organisms and has significantly impacted drug discovery processes by enabling the development of highly selective small-molecule inhibitors and the identification of new therapeutic molecular targets. Despite being nearly a quarter of a century old as a chemoproteomic tool, ABPP has yet to undergo a bibliometric analysis. In order to gauge its scholarly impact and evolution, a bibliometric analysis was performed, comparing all 1919 reported articles with the articles published in the last five years. Through a comprehensive data analysis, including a 5-step workflow, the most influential articles were identified, and their bibliometric parameters were determined. The 1919 analyzed articles span from 1999 to 2022, providing a comprehensive overview of the historical and current state of ABPP research. This analysis presents, for the first time, the characteristics of the most influential ABPP articles, offering valuable insight into the research conducted in this field and its potential future directions. The findings underscore the crucial role of ABPP in drug discovery and novel therapeutic target identification, as well as the need for continued advancements in the development of novel chemical probes and proteomic technologies to further expand the utility of ABPP.

Indexed as

Activity-based probesActivity-based protein profilingAffinity-based probesBibliometric analysisChemical probesDrug discovery

Identifiers

PMID38022804
PMCPMC10676541

What OpenQuestion holds

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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.