Identification and Mutational Analysis of Amino Acid Residues Involved in Dipyridamole Interactions with Human and Caenorhabditis elegans Equilibrative Nucleoside Transporters
Bibliographic record
Abstract
The equilibrative nucleoside transporters, hENT1 and CeENT1 from humans and Caenorhabditis elegans, respectively, are inhibited by nanomolar concentrations of dipyridamole and share a common 11-transmembrane helix (TM) topology. Random mutagenesis and screening by functional complementation in yeast for clones with reduced sensitivities to dipyridamole yielded mutations at Ile429 in TM 11 of CeENT1 and Met33 in TM 1 of hENT1. Mutational analysis of the corresponding residues of both proteins suggested important roles for these residues in competitive inhibition of hENT1 and CeENT1 by dipyridamole. To verify the roles of these residues in dipyridamole interactions, hENT2, which naturally exhibits low dipyridamole sensitivity, was mutated to contain side chains favorable for high affinity dipyridamole binding (i.e. a Met at the TM 1 and/or an Ile at the TM 11 positions). The single mutants exhibited increased hENT2 sensitivity to inhibition by dipyridamole, and the double mutant was the most sensitive, with an IC50 value that was only 2% of that of wild type. Functional analysis of the TM 1 and 11 mutants of hENT1 and CeENT1 revealed that Ala and Thr in the TM 1 and 11 positions, respectively, impaired uridine and adenosine transport and that Leu442 of hENT1 was involved in permeant selectivity. Mechanistic and structural models of dipyridamole interactions with the TM 1 and 11 residues are proposed. This study demonstrated that the corresponding residues in TMs 1 and 11 of hENT1, hENT2, and CeENT1 are important for dipyridamole interactions and nucleoside transport.
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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) | 0.000 | 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 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".