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Record W4406030973 · doi:10.1021/acschembio.4c00450

Functional Characterization of Pathway Inhibitors for the Ubiquitin-Proteasome System (UPS) as Tool Compounds for CRBN and VHL-Mediated Targeted Protein Degradation

2025· article· en· W4406030973 on OpenAlexfundno aff
Martin P. Schwalm, Amelie Menge, Lewis Elson, Francesco Greco, Matthew B. Robers, Susanne Müller, Stefan Knapp

Bibliographic record

VenueACS Chemical Biology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsnot available
FundersJanssen CanadaGenentechInnovative Medicines InitiativeDeutsche ForschungsgemeinschaftStructural Genomics ConsortiumTakeda FoundationDeutschen Konsortium für Translationale KrebsforschungOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsOntario GenomicsGenome CanadaBoehringer IngelheimMcGill UniversityBayerPfizerDeutsches KrebsforschungszentrumBristol-Myers Squibb
KeywordsUbiquitinProteasomeProtein degradationDegradation (telecommunications)Ubiquitin-Protein LigasesChemistryCell biologyCancer researchUbiquitin ligaseBiologyComputational biologyBiochemistryComputer scienceGene

Abstract

fetched live from OpenAlex

Small molecule degraders such as PROteolysis TArgeting Chimeras (PROTACs) and molecular glues are new modalities for drug development and important tools for target validation. When appropriately optimized, both modalities lead to proteasomal degradation of the protein of interest (POI). Due to the complexity of the induced multistep degradation process, controls for degrader evaluation are critical and commonly used in the literature. However, comparative studies and evaluations of cellular potencies of these control compounds have not been published so far. Here, we investigated a diverse set of ubiquitin pathway inhibitors and evaluated their potency and utility within the CRBN and VHL-mediated degradation pathway. We used the HiBiT system to measure the level of target rescue after treatment with the control compounds. In addition, the cell health was assessed using a multiplexed high-content assay. These assays allowed us to determine nontoxic effective concentrations for control experiments and to perform rescue experiments in the absence of cellular toxicity.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.228
Teacher spread0.220 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations12
Published2025
Admission routes1
Has abstractyes

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