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Record W2731703102 · doi:10.1021/jacs.7b04415

Delivery and Release of Small-Molecule Probes in Mitochondria Using Traceless Linkers

2017· article· en· W2731703102 on OpenAlexafffund
Eric K. Lei, Shana O. Kelley

Bibliographic record

VenueJournal of the American Chemical Society · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicATP Synthase and ATPases Research
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsLinkerChemistrySmall moleculeMitochondrionConjugateCytosolBiophysicsMitochondrial matrixCombinatorial chemistryCleavage (geology)BiochemistryEnzymeBiology

Abstract

fetched live from OpenAlex

Mitochondria-penetrating peptides (MPPs) are specific targeting vectors for the localization of small molecules to the mitochondrial matrix. Mitochondrial targeting of small molecules has enabled the development of a number of potential therapeutics and chemical probes. However, the need for covalent conjugation of small molecules to MPPs can negatively affect the activity of the appended cargo against its cellular target. Here, we describe cleavable linkers designed for the traceless release of chemical cargo from MPPs following mitochondrial transit. The cleavage kinetics of a number of disulfides were investigated using a fluorescent reporter system in order to optimize linker stability for mitochondrial release. The stability of mono- and disubstituted disulfides was determined to be sufficient during transit through the cytosol while still allowing for release of the cargo within 24 h. This linker system successfully released the compound Luminespib, an HSP90 inhibitor, which was deactivated by direct MPP conjugation. The releasable conjugate regenerated Luminespib activity and induced mitochondrial phenotypes of HSP90 inhibition. This linker may prove useful in expanding the repertoire of small molecules that can be used with mitochondrial targeting vectors.

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 score0.007
Threshold uncertainty score0.229

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 studies0.0000.001
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 head0.021
GPT teacher head0.302
Teacher spread0.281 · 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
Published2017
Admission routes2
Has abstractyes

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