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Record W4407350032 · doi:10.1021/acschembio.4c00812

Workflow for E3 Ligase Ligand Validation for PROTAC Development

2025· article· en· W4407350032 on OpenAlexfundno aff
Nebojša Miletić, Janik Weckesser, Thorsten Mosler, Rajeshwari Rathore, Marina E. Hoffmann, Paul Gehrtz, Sarah Schlesiger, Ingo V. Hartung, Nicola Berner, Stephanie Wilhelm, Juliane Müller, Bikash Adhikari, Václav Němec, Saran Aswathaman Sivashanmugam, Lewis Elson, Martin P. Schwalm, Lasse Hoffmann, Kamal R. Abdul Azeez, Susanne Müller, Bernhard Küster, Elmar Wolf, Ivan Đikić, Stefan Knapp

Bibliographic record

VenueACS Chemical Biology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsnot available
FundersStructural Genomics ConsortiumLOEWE-Zentrum für Translationale Medizin und PharmakologieDeutschen Konsortium für Translationale KrebsforschungFraunhofer-GesellschaftInnovative Medicines InitiativeTechnische Universität MünchenBundesministerium für Bildung und ForschungDeutsche KrebshilfeHessisches Ministerium für Wissenschaft und KunstDeutsche ForschungsgemeinschaftDeutsches Krebsforschungszentrum
KeywordsWorkflowUbiquitin ligaseDNA ligaseLigand (biochemistry)Computer scienceComputational biologyBusinessProcess managementChemistryUbiquitinBiologyDatabaseBiochemistryReceptorDNA

Abstract

fetched live from OpenAlex

Proteolysis targeting chimeras (PROTACs) have gained considerable attention as a new modality in drug discovery. The development of PROTACs has been mainly focused on using CRBN (Cereblon) and VHL (Von Hippel-Lindau ligase) E3 ligase ligands. However, the considerable size of the human E3 ligase family, newly developed E3 ligase ligands, and the favorable druggability of some E3 ligase families hold the promise that novel degraders with unique pharmacological properties will be designed in the future using this large E3 ligase space. Here, we developed a workflow aiming to improve and streamline the evaluation of E3 ligase ligand efficiency for PROTAC development and the assessment of the corresponding "degradable" target space using broad-spectrum kinase inhibitors and the well-established VHL ligand VH032 as a validation system. Our study revealed VH032 linker attachment points that are highly efficient for kinase degradation as well as some of the pitfalls when using protein degradation as a readout. For instance, cytotoxicity was identified as a major mechanism leading to PROTAC- and VHL-independent kinase degradation. The combination of E3 ligase ligand negative controls, competition by kinase parent compounds, and neddylation and proteasome inhibitors was essential to distinguish between VHL-dependent and -independent kinase degradation events. We share here the findings and limitations of our study and hope that this study will provide guidance for future evaluations of new E3 ligase ligand systems for degrader development.

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)0.000
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 score0.262
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.284
Teacher spread0.272 · 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

Citations17
Published2025
Admission routes1
Has abstractyes

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