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Record W2029204005 · doi:10.1021/bi049135y

Domain−Domain Interactions in the Aminoglycoside Antibiotic Resistance Enzyme AAC(6‘)-APH(2‘ ‘)

2004· article· en· W2029204005 on OpenAlexafffund
David D. Boehr, Denis M. Daigle, Gerard D. Wright

Bibliographic record

VenueBiochemistry · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAminoglycosideAntibioticsPhosphotransferaseEnzymeAntibiotic resistanceFunction (biology)AcetyltransferaseDomain (mathematical analysis)ChemistryPhosphotransferasesBiologyBiochemistryMicrobiologyComputational biologyCell biologyGene

Abstract

fetched live from OpenAlex

The most common determinant of aminoglycoside antibiotic resistance in Gram positive bacterial pathogens, such as Staphylococcus aureus, is a modifying enzyme, AAC(6')-APH(2' '), capable of acetylating and phosphorylating a wide range of antibiotics. This enzyme is unique in that it is composed of two separable modification domains, and although a number of studies have been conducted on the acetyltransferase and phosphotransferase activities in isolation, little is known about the role and impact of domain interactions on antibiotic resistance. Kinetic analysis and in vivo assessment of a number of N- and C-terminal truncated proteins have demonstrated that the two domains operate independently and do not accentuate one another's resistance activity. However, the two domains are structurally integrated, and mutational analysis has demonstrated that a predicted connecting alpha-helix is especially critical for maintaining proper structure and function of both activities. AAC(6')-APH(2' ') detoxifies a staggering array of aminoglycosides, where one or both activities make important contributions depending on the antibiotic. Thus, to overcome antibiotic resistance associated with AAC(6')-APH(2' '), aminoglycosides resistant to modification and/or inhibitors against both activities must be employed. Domain-domain interactions in AAC(6')-APH(2' ') offer a unique target for inhibitor strategies, as we show that their disruption simultaneously inhibits both activities >90%.

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 categoriesMeta-epidemiology (narrow)
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 score0.059
Threshold uncertainty score1.000

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 head0.009
GPT teacher head0.256
Teacher spread0.247 · 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.

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

Citations57
Published2004
Admission routes2
Has abstractyes

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