Evidence map›Paper›PMID 38229751›Full record

ArticleACS medicinal chemistry letters2024

DegraderTCM: A Computationally Sparing Approach for Predicting Ternary Degradation Complexes.

Paolo Rossetti, Giulia Apprato, Giulia Caron, Giuseppe Ermondi, Matteo Rossi Sebastiano

Open access · hybridAbstract read
In one paragraph

Article in ACS medicinal chemistry letters, 2024. 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
2.2field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Bellerophon: An Automated Tool for PROTAC Decomposition.ACS medicinal chemistry letters · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
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 at 1 institution in 1 country.

Paolo RossettiUniversity of Torino, Department of Molecular Biotechnology and Health Sciences, CASSMedChem, Piazza Nizza 44, 10126 Torino, Italy.
Giulia AppratoUniversity of Torino, Department of Molecular Biotechnology and Health Sciences, CASSMedChem, Piazza Nizza 44, 10126 Torino, Italy.ORCID https://orcid.org/0000-0001-6906-2849
Giulia CaronUniversity of Torino, Department of Molecular Biotechnology and Health Sciences, CASSMedChem, Piazza Nizza 44, 10126 Torino, Italy.ORCID https://orcid.org/0000-0002-2417-5900
Giuseppe ErmondiUniversity of Torino, Department of Molecular Biotechnology and Health Sciences, CASSMedChem, Piazza Nizza 44, 10126 Torino, Italy.ORCID https://orcid.org/0000-0003-3710-3102
Matteo Rossi SebastianoUniversity of Torino, Department of Molecular Biotechnology and Health Sciences, CASSMedChem, Piazza Nizza 44, 10126 Torino, Italy.ORCID https://orcid.org/0000-0002-9925-1904
University of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteolysis targeting chimeras (PROTACs or degraders) represent a novel therapeutic modality that has raised interest thanks to promising results and currently undergoing clinical testing. PROTACs induce the selective proteasomal degradation of undesired proteins by the formation of ternary complexes (TCs). Having knowledge of the 3D structure of TCs is crucial for the design of PROTAC drugs. Here, we describe DegraderTCM, a new computational method for modeling PROTAC-mediated TCs that requires low computational power and provides sound results in a short time span. We validated DegraderTCM against a selected set of experimentally determined structures and defined a method to predict the PROTAC degradation activity based on the computed TC structure. Finally, we modeled TCs of known degraders holding significance for defining the method's applicability domain. A retrospective analysis of structure-activity relationships unveiled possibilities for utilizing DegraderTCM in the initial stages of designing novel PROTAC drugs.

Identifiers

PMID38229751
PMCPMC10788944
OpenAlexW4389663655

What OpenQuestion holds

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LicenceCC BY
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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.