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Record W4353045940 · doi:10.1021/acs.jmedchem.2c02132

Discovery of Nanomolar DCAF1 Small Molecule Ligands

2023· article· en· W4353045940 on OpenAlexafffund
Alice Shi Ming Li, Serah Kimani, Brian J. Wilson, Mahmoud Noureldin, Héctor González-Álvarez, Ahmed Mamai, Laurent Hoffer, John P. Guilinger, Ying Zhang, Moritz von Rechenberg, Jeremy S. Disch, Christopher J. Mulhern, Belinda L. Slakman, John W. Cuozzo, Aiping Dong, Gennady Poda, Mohammed Mohammed, Punit Saraon, Manish Mittal, Pratik Modh, V. Rathod, Bhashant Patel, Suzanne Ackloo, Vijayaratnam Santhakumar, Magdalena M. Szewczyk, Dalia Baršytė-Lovejoy, C.H. Arrowsmith, Richard Marcellus, Marie-Aude Guié, Anthony D. Keefe, Peter J. Brown, Levon Halabelian, Rima Al‐awar, Masoud Vedadi

Bibliographic record

VenueJournal of Medicinal Chemistry · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkStructural Genomics ConsortiumUniversity of TorontoOntario Institute for Cancer Research
FundersNational Institute of General Medical SciencesOntario Genomics InstituteOffice of ScienceRelay TherapeuticsOntario Institute for Cancer ResearchUniversity of TorontoEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaANational Institutes of HealthOntario GenomicsGenome CanadaArgonne National LaboratoryU.S. Department of EnergyMcGill UniversityGenentechGovernment of OntarioBayerPfizerBristol-Myers Squibb
KeywordsChemistryDrug discoverySmall moleculeNanotechnologyBiochemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide DCAF1 is a substrate receptor of two distinct E3 ligases (CRL4 DCAF1 and EDVP), plays a critical physiological role in protein degradation, and is considered a drug target for various cancers. Antagonists of DCAF1 could be used toward the development of therapeutics for cancers and viral treatments. We used the WDR domain of DCAF1 to screen a 114-billion-compound DNA encoded library (DEL) and identified candidate compounds using similarity search and machine learning. This led to the discovery of a compound (Z1391232269) with an SPR K D of 11 μM. Structure-guided hit optimization led to the discovery of OICR-8268 ( 26e ) with an SPR K D of 38 nM and cellular target engagement with EC 50 of 10 μM as measured by cellular thermal shift assay (CETSA). OICR-8268 is an excellent tool compound to enable the development of next-generation DCAF1 ligands toward cancer therapeutics, further investigation of DCAF1 functions in cells, and the development of DCAF1-based PROTACs.

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 score0.002
Threshold uncertainty score0.362

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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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

Citations65
Published2023
Admission routes2
Has abstractyes

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