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Record W1998063413 · doi:10.7554/elife.03574

Discovery of a small molecule that inhibits bacterial ribosome biogenesis

2014· article· en· W1998063413 on OpenAlexafffund
Jonathan Stokes, Joseph H. Davis, Chand S. Mangat, James R. Williamson, Eric D. Brown

Bibliographic record

VenueeLife · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsMcMaster University
FundersNational Institute of General Medical SciencesNational Institutes of HealthCanada Research ChairsCanadian Institutes of Health ResearchOntario Council on Graduate Studies, Council of Ontario UniversitiesNatural Sciences and Engineering Research Council of CanadaMcMaster UniversityJane Coffin Childs Memorial Fund for Medical Research
KeywordsBiogenesisRibosomeRibosome biogenesisSmall moleculeComputational biologyBiologyChemical biologyStructural biologyCell biologyChemistryGeneticsRNAGene

Abstract

fetched live from OpenAlex

While small molecule inhibitors of the bacterial ribosome have been instrumental in understanding protein translation, no such probes exist to study ribosome biogenesis. We screened a diverse chemical collection that included previously approved drugs for compounds that induced cold sensitive growth inhibition in the model bacterium Escherichia coli. Among the most cold sensitive was lamotrigine, an anticonvulsant drug. Lamotrigine treatment resulted in the rapid accumulation of immature 30S and 50S ribosomal subunits at 15 °C. Importantly, this was not the result of translation inhibition, as lamotrigine was incapable of perturbing protein synthesis in vivo or in vitro. Spontaneous suppressor mutations blocking lamotrigine activity mapped solely to the poorly characterized domain II of translation initiation factor IF2 and prevented the binding of lamotrigine to IF2 in vitro. This work establishes lamotrigine as a widely available chemical probe of bacterial ribosome biogenesis and suggests a role for E. coli IF2 in ribosome assembly.

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 score0.489

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 head0.014
GPT teacher head0.214
Teacher spread0.201 · 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

Citations92
Published2014
Admission routes2
Has abstractyes

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