Mutation of Residue 33 of Human Equilibrative Nucleoside Transporters 1 and 2 Alters Sensitivity to Inhibition of Transport by Dilazep and Dipyridamole
Bibliographic record
Abstract
Human equilibrative nucleoside transporters (hENT) 1 and 2 differ in that hENT1 is inhibited by nanomolar concentrations of dipyridamole and dilazep, whereas hENT2 is 2 and 3 orders of magnitude less sensitive, respectively. When a yeast expression plasmid containing the hENT1 cDNA was randomly mutated and screened by phenotypic complementation in Saccharomyces cerevisiae to identify mutants with reduced sensitivity to dilazep, clones with a point mutation that converted Met33 to Ile (hENT1-M33I) were obtained. Characterization of the mutant protein in S. cerevisiae and Xenopus laevis oocytes revealed that the mutant had less than one-tenth the sensitivity to dilazep and dipyridamole than wild type hENT1, with no change in nitrobenzylmercaptopurine ribonucleoside (NBMPR) sensitivity or apparent uridine affinity. To determine whether the reciprocal mutation in hENT2 (Ile33 to Met) also altered sensitivity to dilazep and dipyridamole, hENT2-I33M was created by site-directed mutagenesis. Although the resulting mutant (hENT2-I33M) displayed >10-fold higher dilazep and dipyridamole sensitivity and >8-fold higher uridine affinity compared with wild type hENT2, it retained insensitivity to NBMPR. These data established that mutation of residue 33 (Met versus Ile) of hENT1 and hENT2 altered the dilazep and dipyridamole sensitivities in both proteins, suggesting that a common region of inhibitor interaction has been identified.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".