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Record W2029345540 · doi:10.1021/ml300467n

Synthesis, Optimization, and Evaluation of Novel Small Molecules as Antagonists of WDR5-MLL Interaction

2013· article· en· W2029345540 on OpenAlexaff
Yuri Bolshan, Matthäus Getlik, Ekaterina Kuznetsova, Gregory A. Wasney, Taraneh Hajian, Gennadiy Poda, Kong T. Nguyen, Hong Wu, L. Dombrovski, Aiping Dong, Guillermo Senisterra, Matthieu Schapira, C.H. Arrowsmith, Peter J. Brown, Rima Al‐awar, Masoud Vedadi, David Smil

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsStructural Genomics ConsortiumOntario Institute for Cancer ResearchUniversity of Toronto
Fundersnot available
KeywordsMethyltransferaseAntagonismSmall moleculeAntagonistEpigeneticsHistone methyltransferaseChemistryTransferaseProtein subunitComputational biologyLysineFunction (biology)Histone H3Protein–protein interactionPharmacologyEnzymeStereochemistryBiochemistryBiologyCell biologyMethylationAmino acidReceptorGene

Abstract

fetched live from OpenAlex

The WD40-repeat protein WDR5 plays a critical role in maintaining the integrity of MLL complexes and fully activating their methyltransferase function. MLL complexes, the trithorax-like family of SET1 methyltransferases, catalyze trimethylation of lysine 4 on histone 3, and they have been widely implicated in various cancers. Antagonism of WDR5 and MLL subunit interaction by small molecules has recently been presented as a practical way to inhibit activity of the MLL1 complex, and N-(2-(4-methylpiperazin-1-yl)-5-substituted-phenyl) benzamides were reported as potent and selective antagonists of such an interaction. Here, we describe the protein crystal structure guided optimization of prototypic compound 2 (K dis = 7 μM), leading to identification of more potent antagonist 47 (K dis = 0.3 μM).

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 score0.008
Threshold uncertainty score0.466

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 head0.019
GPT teacher head0.273
Teacher spread0.254 · 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

Citations74
Published2013
Admission routes1
Has abstractyes

Explore more

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