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Record W2769066285 · doi:10.1038/s41467-017-01319-4

Multicomponent mapping of boron chemotypes furnishes selective enzyme inhibitors

2017· article· en· W2769066285 on OpenAlexafffund
Joanne Tan, Armand B. Cognetta, Diego B. Diaz, Kenneth M. Lum, Shinya Adachi, Soumajit Kundu, Benjamin F. Cravatt, Andrei K. Yudin

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsUniversity of Toronto
FundersNational Institute on Drug AbuseNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsEnzymeChemotypeSerineChemistryHeteroatomCombinatorial chemistrySerine hydrolaseBiochemistryIn vitroSmall moleculeOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Heteroatom-rich organoboron compounds have attracted attention as modulators of enzyme function. Driven by the unmet need to develop chemoselective access to boron chemotypes, we report herein the synthesis of α- and β-aminocyano(MIDA)boronates from borylated carbonyl compounds. Activity-based protein profiling of the resulting β-aminoboronic acids furnishes selective and cell-active inhibitors of the (ox)lipid-metabolizing enzyme α/β-hydrolase domain 3 (ABHD3). The most potent compound displays nanomolar in vitro and in situ IC 50 values and fully inhibits ABHD3 activity in human cells with no detectable cross-reactivity against other serine hydrolases. These findings demonstrate that synthetic methods that enhance the heteroatom diversity of boron-containing molecules within a limited set of scaffolds accelerate the discovery of chemical probes of human enzymes.

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 score0.068
Threshold uncertainty score0.322

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 science0.0010.000
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 head0.016
GPT teacher head0.285
Teacher spread0.270 · 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

Citations37
Published2017
Admission routes2
Has abstractyes

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