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Record W2976071796 · doi:10.1158/1538-7445.am2018-1646

Abstract 1646: Discovery and characterization of BAY-6035, a novel benzodiazepine-based SMYD3 inhibitor

2018· article· en· W2976071796 on OpenAlexaff
Stefan Gradl, H. Steuber, Jörg Weiske, Norbert Schmees, Stephan Siegel, Detlef Stoeckigt, Clara D. Christ, Fengling Li, Shawna Organ, Dalia Baršytė-Lovejoy, Magdalena M. Szewczyk, Viacheslav V. Trush, Masoud Vedadi, C.H. Arrowsmith, Peter J. Brown, Manfred Husemann, Amaury E. Fernández‐Montalván, Volker Badock, Marcus Bauser, Andrea Haegebarth, Ingo V. Hartung, Carlo Stresemann

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsStructural Genomics Consortium
Fundersnot available
KeywordsKinaseMethyltransferaseDrug discoveryProtein kinase domainChemistryCancer researchBiologyCell biologyMethylationBiochemistryGeneMutant

Abstract

fetched live from OpenAlex

Abstract SMYD3 (SET and MYND domain-containing protein 3) is a protein lysine methyltransferase (PKMT) which was initially described as H3K4 methyltransferase involved in transcriptional regulation. SMYD3 has recently been reported to methylate and regulate several non-histone cancer relevant proteins such as mitogen-activated protein kinase kinase kinase 2 (MAP3K2), vascular endothelial growth factor receptor 1 (VEGFR1), and the human epidermal growth factor receptor 2 (HER2). In addition overexpression of SMYD3 has been linked to poor prognosis in certain cancers, thus supporting a possible oncogenic role for SMYD3 and making it an attractive target for anticancer drug development. Here we report the discovery of a novel potent and selective SMYD3 inhibitor series. We performed a thermal shift assay based (TSA) high throughput screening followed by extensive biophysical validation resulting in identification of a benzodiazepine-based SMYD3 inhibitor series. The co-crystallization structures revealed that this series binds to the substrate binding site and occupies the hydrophobic pocket for lysine binding using an unprecedented hydrogen bond pattern. The competitive behavior of the inhibitor in biochemical assays was consistent with the binding mode observed in the crystal structure. Further optimization generated BAY-6035, which showed improved nanomolar potency and was selective against kinases and other PKMTs. Furthermore, BAY-6035 specifically inhibited methylation of MAP3K2 by SMYD3 in a cellular assay with similar potency. In summary, BAY-6035 is a novel selective and potent SMYD3 inhibitor probe and will foster the exploration of the biologic role of SMYD3 in diseased and non-diseased tissues. Citation Format: Stefan Gradl, Holger Steuber, Jörg Weiske, Norbert Schmees, Stephan Siegel, Detlef Stoeckigt, Clara D. Christ, Fengling Li, Shawna Organ, Dalia Barsyte-Lovejoy, Magdalena M. Szewczyk, Steven Kennedy, Viacheslav Trush, Masoud Vedadi, Cheryl H. Arrowsmith, Peter J. Brown, Manfred Husemann, Amaury E. Fernandez-Montalvan, Volker Badock, Marcus Bauser, Andrea Haegebarth, Ingo V. Hartung, Carlo Stresemann. Discovery and characterization of BAY-6035, a novel benzodiazepine-based SMYD3 inhibitor [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1646.

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 score0.004

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 head0.048
GPT teacher head0.366
Teacher spread0.318 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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