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Record W2290513946 · doi:10.1021/acschembio.5b01070

Structural Analysis of the Tobramycin and Gentamicin Clinical Resistome Reveals Limitations for Next-generation Aminoglycoside Design

2016· article· en· W2290513946 on OpenAlexafffund
Angelia V. Bassenden, Dmitry A. Rodionov, Kun Shi, Albert M. Berghuis

Bibliographic record

VenueACS Chemical Biology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsMcGill University
FundersInstitute of Infection and ImmunityCanada Research Chairs
KeywordsTobramycinAminoglycosideResistomeGentamicinAntibioticsMicrobiologyBiologyAntibiotic resistance

Abstract

fetched live from OpenAlex

Widespread use and misuse of antibiotics has allowed for the selection of resistant bacteria capable of avoiding the effects of antibiotics. The primary mechanism for resistance to aminoglycosides, a broad-spectrum class of antibiotics, is through covalent enzymatic modification of the drug, waning their bactericidal effect. Tobramycin and gentamicin are two medically important aminoglycosides targeted by several different resistance factors, including aminoglycoside 2″-nucleotidyltransferase [ANT(2″)], the primary cause of aminoglycoside resistance in North America. We describe here two crystal structures of ANT(2″), each in complex with AMPCPP, Mn(2+), and either tobramycin or gentamicin. Together these structures outline ANT(2″)'s specificity for clinically used substrates. Importantly, these structures complete our structural knowledge for the set of enzymes that most frequently confer clinically observed resistance to tobramycin and gentamicin. Comparison of tobramycin and gentamicin binding to enzymes in this resistome, as well as to the intended target, the bacterial ribosome, reveals surprising diversity in observed drug-target interactions. Analysis of the diverse binding modes informs that there are limited opportunities for developing aminoglycoside analogs capable of evading resistance.

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)0.001
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 score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.164
GPT teacher head0.361
Teacher spread0.198 · 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

Citations25
Published2016
Admission routes2
Has abstractyes

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