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Record W2318836896 · doi:10.1021/ja110246u

Maximizing the Therapeutic Window of an Antimicrobial Drug by Imparting Mitochondrial Sequestration in Human Cells

2011· article· en· W2318836896 on OpenAlexafffund
Mark P. Pereira, Shana O. Kelley

Bibliographic record

VenueJournal of the American Chemical Society · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAntimicrobialChemistryToxicityStaphylococcus aureusAntibioticsDrugBacteriaMitochondrial toxicityPeptideMicrobiologyPharmacologyBiochemistryBiology

Abstract

fetched live from OpenAlex

The number of antimicrobial agents available for use in humans is limited by the difficulty of discovering chemical agents with selective toxicity to bacterial targets. Numerous small molecule inhibitors have potential as antimicrobial agents, yet their use has been prevented by high levels of toxic cross-reactivity in human cells. For example, methotrexate (Mtx) is an effective antimetabolite that exerts its effects by inhibiting DHFR. It is a potent antibacterial when accumulated intracellularly, but toxicity in human cells limits clinical utility in infectious disease treatment. Here, we describe peptide conjugates of Mtx that are sequestered into the mitochondria of human cells (mt-Mtx). This alteration in localization of Mtx, which directs it away from its enzyme target, decreases its toxicity in human cells by a factor of 10(3). Mt-Mtx, however, maintains activity against a variety of pathogenic gram-positive organisms, including methicillin-resistant Staphylococcus aureus (MRSA). The results from this proof-of-principle study describe a novel methodology for augmenting the antibacterial efficacy of drugs amenable to peptide conjugation while simultaneously decreasing their toxicity to the host organism.

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 score0.002
Threshold uncertainty score0.267

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 head0.015
GPT teacher head0.258
Teacher spread0.243 · 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

Citations61
Published2011
Admission routes2
Has abstractyes

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