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Record W2558365723 · doi:10.1107/s2053273314091797

Virtual Screening of Histone Lysine Demethylase(JMJD2) identifies new inhibitors

2014· article· en· W2558365723 on OpenAlexaff
Magdalena Korczynska, Daniel Le, Elisabet Gregori‐Puigjané, Noah Younger, T. Krojer, Anthony Tumber, Udo Oppermann, Danica Galonić Fujimori, Brian K. Shoichet

Bibliographic record

VenueActa Crystallographica Section A Foundations and Advances · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDemethylaseSmall moleculeHistoneVirtual screeningChemistryDocking (animal)BiochemistryEnzymeHistone H3LysineHistone methylationSubfamilyComputational biologyBiologyDrug discoveryAmino acidGeneGene expressionDNA methylation

Abstract

fetched live from OpenAlex

The JmjC domain-containing proteins are hydroxylases that confer posttranslational modifications on histone tails, by removing methylation marks on methylated lysine residues. This serves to either promote or repress gene transcription. The JMJD2A-D family members include the enzyme Jumonji domain 2C (JMJD2C), which specifically demethylates di- and trimethylated histone H3 at Lys 9 or Lys 36.[1] Dysregulation of JMJD2C has been implicated in prostate, colonic, and breast cancer as the demethylase can modify the expression levels of oncogenes.[2] The goal of the present study was to identify potent and selective small-molecule inhibitors of JMJD2C, to be used as chemical biology tools to further investigate the role of JMJD2C in cell proliferation and survival. Using high-resolution crystal structures of the JMJD2 subfamily members as templates, we have performed a small molecule virtual docking screen. From the ~3 million molecules that were docked, this experiment identified 21 compounds as possible leads. These compounds were tested against JMJD2C in enzymatic assays and here we report an overall hit rate of 76%, with 8 compounds demonstrating an IC50 of 176μM to 1.18μM. A molecule containing a salicylate core was selected as a candidate for optimization and thus far we have completed several rounds of iterative target-specific compound docking, hybrid molecule design, compound synthesis and in vitro characterization. Notably, our method demonstrated a substantial increase in potency when we linked two docked fragments together and further derivatized this new scaffold, through which we have successfully derived a 65nM inhibitor of JMJD2C. A compound representing the inhibitor scaffold has been co-crystallized with JMJD2A to a resolution of 2.4 Å. In the crystal structure each asymmetric unit contains two JMJD2A monomers, each bound to a single inhibitor molecule. This complex-structure superposes well with the docked pose for the hybrid series of compounds. We are now focusing our efforts on identifying an inhibitor that is selective for the JMJD2 family over other JmjC domain-containing proteins.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.283
Teacher spread0.274 · 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 designSimulation or modeling
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

Citations0
Published2014
Admission routes1
Has abstractyes

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