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Record W2597614218 · doi:10.1002/chem.201701329

Tunable GLUT–Hexose Binding and Transport via Modulation of Hexose C‐3 Hydrogen‐Bonding Capabilities

2017· article· en· W2597614218 on OpenAlexafffund
Venkata Pavan Kumar Kondapi, Mohamad Soueidan, C. I. Cheeseman, F. G. West

Bibliographic record

VenueChemistry - A European Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Cancer Society
KeywordsHexoseGLUT1Glucose transporterChemistryHydrogen bondMediated transportMannitolGlucose Transporter Type 1BiochemistryStereochemistryEnzymeMoleculeInsulinOrganic chemistryBiologyMembrane

Abstract

fetched live from OpenAlex

The importance of the hydrogen bonding interactions in the GLUT-hexose binding process (GLUT=hexose transporter) has been demonstrated by studying the binding of structurally modified d-fructose analogues to GLUTs, and in one case its transport into cells. The presence of a hydrogen bond donor at the C-3 position of 2,5-anhydro-d-mannitol derivatives is essential for effective binding to GLUT5 and transport into tumor cells. Surprisingly, installation of a group that can function only as a hydrogen bond acceptor at C-3 resulted in selective recognition by GLUT1 rather than GLUT5. A fluorescently labelled analogue clearly showed GLUT-mediated transport and low efflux properties of the probe. This study reveals that a single positional modification of a 2,5-anhydro-d-mannitol derivative is sufficient to switch its binding preference from GLUT5 to GLUT1, and uncovers general scaffolds that are suitable for the potential selective delivery of molecular payloads into tumor cells via GLUT transport machinery.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.019
GPT teacher head0.249
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2017
Admission routes2
Has abstractyes

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Same venueChemistry - A European JournalSame topicDiet, Metabolism, and DiseaseFrench-language works237,207