Residues 334 and 338 in Transmembrane Segment 8 of Human Equilibrative Nucleoside Transporter 1 Are Important Determinants of Inhibitor Sensitivity, Protein Folding, and Catalytic Turnover
Bibliographic record
Abstract
Equilibrative nucleoside transporters (ENTs) are important for the metabolic salvage of nucleosides and the cellular uptake of antineoplastic and antiviral nucleoside analogs. Human equilibrative nucleoside transporter 1 (hENT1) is inhibited by nanomolar concentrations of structurally diverse compounds, including dipyridamole, dilazep, nitrobenzylmercaptopurine ribonucleoside (NBMPR), draflazine, and soluflazine. Random mutagenesis and screening by functional complementation for inhibitor-resistant mutants in yeast revealed mutations at Phe-334 and Asn-338. Both residues are predicted to lie in transmembrane segment 8 (TM 8), which contains residues that are highly conserved in the ENT family. F334Y displayed increased V(max) values that were attributed to increased rates of catalytic turnover, and N338Q and N338C displayed altered membrane distributions that appeared to be because of protein folding defects. Mutations of Phe-334 or Asn-338 impaired interactions with dilazep and dipyridamole, whereas mutations of Asn-338 impaired interactions with draflazine and soluflazine. A helical wheel projection of TM 8 predicted that Phe-334 and Asn-338 lie in close proximity to other highly conserved and/or hydrophilic residues, suggesting that they form part of a structurally important region that influences interactions with inhibitors, protein folding, and rates of conformational change during the transport cycle.
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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) | 0.001 | 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".