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Record W3162028161 · doi:10.1021/acs.jmedchem.1c00146

Design, Synthesis, and Evaluation of WD-Repeat-Containing Protein 5 (WDR5) Degraders

2021· article· en· W3162028161 on OpenAlexaff
Anja Dölle, Bikash Adhikari, Andreas Krämer, Janik Weckesser, Nicola Berner, Lena M. Berger, Mathias Diebold, Magdalena M. Szewczyk, Dalia Baršytė-Lovejoy, C.H. Arrowsmith, Jakob Gebel, Frank Löhr, Volker Dötsch, Martin Eilers, Stephanie Heinzlmeir, Bernhard Küster, Christoph Sotriffer, Elmar Wolf, Stefan Knapp

Bibliographic record

VenueJournal of Medicinal Chemistry · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkStructural Genomics ConsortiumUniversity of Toronto
FundersDeutsche KrebshilfeBundesministerium für Bildung und ForschungH2020 European Research CouncilDeutsche Forschungsgemeinschaft
KeywordsChemistryMethyltransferaseHistoneLinkerMethylationEpigeneticsProtein biosynthesisAcetylationComputational biologyGeneCell biologyBiochemistryBiology

Abstract

fetched live from OpenAlex

Histone H3K4 methylation serves as a post-translational hallmark of actively transcribed genes and is introduced by histone methyltransferase (HMT) and its regulatory scaffolding proteins. One of these is the WD-repeat-containing protein 5 (WDR5) that has also been associated with controlling long noncoding RNAs and transcription factors including MYC. The wide influence of dysfunctional HMT complexes and the typically upregulated MYC levels in diverse tumor types suggested WDR5 as an attractive drug target. Indeed, protein-protein interface inhibitors for two protein interaction interfaces on WDR5 have been developed. While such compounds only inhibit a subset of WDR5 interactions, chemically induced proteasomal degradation of WDR5 might represent an elegant way to target all oncogenic functions. This study presents the design, synthesis, and evaluation of two diverse WDR5 degrader series based on two WIN site binding scaffolds and shows that linker nature and length strongly influence degradation efficacy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.025
GPT teacher head0.282
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), 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

Citations84
Published2021
Admission routes1
Has abstractyes

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