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Record W3174184405 · doi:10.1039/d1sc02143e

Cellular delivery of dinucleotides by conjugation with small molecules: targeting translation initiation for anticancer applications

2021· article· en· W3174184405 on OpenAlexaff
Natalia Kleczewska, Pawel J. Sikorski, Zofia Warminska, Łukasz Markiewicz, Renata Kasprzyk, Natalia Baran, Karina Kwapiszewska, Aneta Karpińska, Jarosław Michalski, Robert Hołyst, Joanna Kowalska, Jacek Jemielity

Bibliographic record

VenueChemical Science · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsBureau de Coopération Interuniversitaire
FundersNarodowe Centrum Badań i RozwojuNarodowym Centrum NaukiFundacja na rzecz Nauki Polskiej
KeywordsEIF4EChemistrySmall moleculeTranslation (biology)Computational biologyLigand (biochemistry)Cell biologyBiochemistryBiologyMessenger RNAReceptorGene

Abstract

fetched live from OpenAlex

and could counteract elevated levels of eIF4E in cancer cells; however, transformation of these compounds into therapeutic agents remains challenging - they do not easily penetrate into cells and are susceptible to enzymatic cleavage. Here, we tested the potential of several small molecule ligands - folic acid, biotin, glucose, and cholesterol - to deliver both hydrolyzable and cleavage-resistant cap analogs into cells. A broad structure-activity relationship (SAR) study using model fluorescent probes and cap-ligand conjugates showed that cholesterol greatly facilitates uptake of cap analogs without disturbing the interactions with eIF4E. The most potent cholesterol conjugate identified showed apoptosis-mediated cytotoxicity towards cancer cells.

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 score0.299
Threshold uncertainty score0.207

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 head0.012
GPT teacher head0.252
Teacher spread0.240 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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