Evidence map›Paper›PMID 36706315›Full record

ReviewJournal of the American Chemical Society2023

Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence.

Miquel Duran-Frigola, Marko Cigler, Georg E Winter

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of the American Chemical Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
6.6field-weighted citation impact, top 3% of its field
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

16 citing papers in PubMed, 43 citations in OpenAlex.

  1. Review
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  3. Proteomics-Driven Strategies for Proximity-Inducing Drug Discovery.Angewandte Chemie (International ed. in English) · 2026
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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

3 authors at 1 institution in 1 country.

Miquel Duran-FrigolaCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria.
Marko CiglerCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria.
Georg E WinterCeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria.ORCID 0000-0001-6606-1437
Austrian Academy of Sciences · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) promises to overcome some of these limitations. In brief, TPD is dependent on small molecules that induce the proximity between a protein of interest (POI) and an E3 ubiquitin ligase, causing ubiquitination and degradation of the POI. In this perspective, we want to reflect on current challenges in the field, and discuss how advances in multiomics profiling, artificial intelligence, and machine learning (AI/ML) will be vital in overcoming them. The presented roadmap is discussed in the context of small-molecule degraders but is equally applicable for other emerging proximity-inducing modalities.

Indexed as

Artificial IntelligenceMultiomicsProteolysisHumansUbiquitinationUbiquitin-Protein LigasesUbiquitin-Protein Ligases

Identifiers

PMID36706315
PMCPMC9912273
OpenAlexW4318257682

What OpenQuestion 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 OpenQuestion graph.