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Record W2740828846 · doi:10.1093/femsre/fux032

Na+-NQR (Na+-translocating NADH:ubiquinone oxidoreductase) as a novel target for antibiotics

2017· review· en· W2740828846 on OpenAlexafffund
Pavel Dibrov, Elena Dibrov, Grant N. Pierce

Bibliographic record

VenueFEMS Microbiology Reviews · 2017
Typereview
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsSt. Boniface HospitalUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsOxidoreductaseBiologyEnzymeAntibioticsBiochemistryMicrobiologyPathogenAntimicrobial

Abstract

fetched live from OpenAlex

The recent breakthrough in structural studies on Na+-translocating NADH:ubiquinone oxidoreductase (Na+-NQR) from the human pathogen Vibrio cholerae creates a perspective for the systematic design of inhibitors for this unique enzyme, which is the major Na+ pump in aerobic pathogens. Widespread distribution of Na+-NQR among pathogenic species, its key role in energy metabolism, its relation to virulence in different species as well as its absence in eukaryotic cells makes this enzyme especially attractive as a target for prospective antibiotics. In this review, the major biochemical, physiological and, especially, the pharmacological aspects of Na+-NQR are discussed to assess its 'target potential' for drug development. A comparison to other primary bacterial Na+ pumps supports the contention that NQR is a first rate prospective target for a new generation of antimicrobials. A new, narrowly targeted furanone inhibitor of NQR designed in our group is presented as a molecular platform for the development of anti-NQR remedies.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.108
GPT teacher head0.369
Teacher spread0.261 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations52
Published2017
Admission routes2
Has abstractyes

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