Polyamine Transport by the Polyspecific Organic Cation Transporters OCT1, OCT2, and OCT3
Bibliographic record
Abstract
Polyamines are ubiquitous organic cations implicated in many physiological processes. Because they are positively charged at physiological pH, carrier-mediated systems are necessary for effective membrane permeation, but the identity of specific polyamine transporter proteins in eukaryotic cells remains unclear. Polyspecific organic cation transporters (OCTs) interact with many natural and xenobiotic monovalent cations and have been reported to transport dicationic compounds, including the short polyamine putrescine. In this study, we used Xenopus oocytes expressing mammalian OCT1 (SLC22A1), OCT2 (SLC22A2), or OCT3 (SLC22A3) to assess binding and transport of longer-chain polyvalent polyamines. In OCT-expressing oocytes, [(3)H]MPP(+) uptake rates were 15- to 35-fold higher than in noninjected oocytes, whereas those for [(3)H]spermidine increased more modestly above the background, up to 3-fold. This reflected up to 20-fold lower affinity for spermidine than for MPP(+); thus, K(0.5) for MPP(+) was ~50 μM in OCT1, ~170 μM in OCT2, and ~60 μM in OCT3, whereas for spermidine, K(0.5) was ~1 mM in OCT1, OCT2, and OCT3. J(max) values for MPP(+) and spermidine were within the same range, suggesting that both compounds are transported at a similar turnover rate. To gain further insight into OCT substrate specificity, we screened a selection of structural polyamine analogues for effect on [(3)H]MPP(+) uptake. In general, blocking potency increased with overall hydrophobic character, which indicates that, as for monovalent cations, hydrophobicity is a major requirement for recognition in polyvalent OCT substrates and inhibitors. Our results demonstrate that the natural polyamines are low affinity, but relatively high turnover, substrates for OCTs. The identification of OCTs as polyamine transport systems may contribute to further understanding of the mechanisms involved in polyamine homeostasis and aid in the design of polyamine-like OCT-targeted drugs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".