Towards Selective Binding to the GLUT5 Transporter: Synthesis, Molecular Dynamics and In Vitro Evaluation of Novel C-3-Modified 2,5-Anhydro-D-mannitol Analogs
Bibliographic record
Abstract
Deregulation and changes in energy metabolism are emergent and important biomarkers of cancer cells. The uptake of hexoses in cancer cells is mediated by a family of facilitative hexose membrane-transporter proteins known as Glucose Transporters (GLUTs). In the clinic, numerous breast cancers do not show elevated glucose metabolism (which is mediated mainly through the GLUT1 transporter) and may use fructose as an alternative energy source. The principal fructose transporter in most cancer cells is GLUT5, and its mRNA was shown to be elevated in human breast cancer. This offers an alternative strategy for early detection using fructose analogs. In order to selectively scout GLUT5 binding-pocket requirements, we designed, synthesized and screened a new class of fructose mimics based upon the 2,5-anhydromannitol scaffold. Several of these compounds display low millimolar IC50 values against the known high-affinity 18F-labeled fructose-based probe 6-deoxy-6-fluoro-D-fructose (6-FDF) in murine EMT6 breast cancer cells. In addition, this work used molecular docking and molecular dynamics simulations (MD) with previously reported GLUT5 structures to gain better insight into hexose–GLUT interactions with selected ligands governing their preference for GLUT5 compared to other GLUTs. The improved inhibition of these compounds, and the refined model for their binding, set the stage for the development of high-affinity molecular imaging probes targeting cancers that express the GLUT5 biomarker.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".