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Record W2042675788 · doi:10.7164/antibiotics.55.407

Identifying Protein Kinase Inhibitors Using an Assay Based on Inhibition of Aerial Hyphae Formation in Streptomyces.

2002· article· en· W2042675788 on OpenAlexaff
Barbara Waters, Geeta Saxena, Yangsheng Wanggui, DAVID A. KAU, Stephen K. Wrigley, Richard W. Stokes, Julian Davies

Bibliographic record

VenueThe Journal of Antibiotics · 2002
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAntimycobacterialStreptomycesKinaseProtein kinase ABiochemistryBiologyMicrobiologyHyphaBacteriaChemistryMycobacterium tuberculosisTuberculosisGenetics

Abstract

fetched live from OpenAlex

We have identified a strain of Streptomyces in which aerial hyphae formation appears to be especially sensitive to inhibition by protein kinase inhibitors. Using this assay, a number of bacterial cultures have been screened and novel inhibitors of eukaryotic protein kinases have been identified. Since M. tuberculosis possesses multiple eukaryotic-like protein kinase genes, we tested the active kinase inhibitors for the inhibition of mycobacterial growth and obtained several potent compounds. This identifies a new biochemical class of antimycobacterial agents.

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)0.001
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 score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.042
GPT teacher head0.271
Teacher spread0.230 · 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

Citations55
Published2002
Admission routes1
Has abstractyes

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