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Record W4414863170 · doi:10.1038/s41467-025-63928-8

Discovery of a CNS active GSK3 degrader using orthogonally reactive linker screening

2025· article· en· W4414863170 on OpenAlexaff
Andreas Holmqvist, Nur Mehpare Kocatürk, Christina Duncan, Jennifer Riley, Steven Baginski, Graham P. Marsh, Joel O. Cresser-Brown, Hannah J. Maple, Kristiina Juvonen, Gajanan Sathe, Nicola Morrice, Calum Sutherland, Kevin D. Read, William Farnaby

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsDiscovery Centre
FundersBiotechnology and Biological Sciences Research CouncilEngineering and Physical Sciences Research CouncilResearch Councils UKDiabetes UKUK Research and InnovationUniversity of DundeeWellcome TrustMedical Research CouncilDirectorate for Biological SciencesWellcome
KeywordsDrug discoveryLinkerIn vivoGSK-3DruggabilityBifunctionalDNA ligaseUbiquitin ligase

Abstract

fetched live from OpenAlex

Bifunctional targeted protein degraders, also known as Proteolysis Targeting Chimeras (PROTACs), are an emerging drug modality that may offer a new approach for treating neurodegenerative diseases. Identifying chemical starting points for PROTACs remains a largely empirical process and the design rules for identifying Central Nervous System (CNS) active PROTACs have yet to be established. Here we demonstrate a concept of using orthogonally reactive linker reagents, that allow the construction of screening libraries whereby the E3 ligase binder, the target protein binder and the linker can be simultaneously varied and tested directly in cellular assays. This approach enabled the discovery of Glycogen Synthase Kinase 3 (GSK3) PROTACs which are CNS in vivo active in female mice. Our findings provide opportunities to investigate the role of GSK3 paralogs in cellular and in vivo disease models and for the rapid discovery of in vivo quality bifunctional chemical probes for CNS disease concepts.

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 score0.079
Threshold uncertainty score0.415

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 head0.022
GPT teacher head0.325
Teacher spread0.303 · 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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