Tricyclic compounds inhibit the OATP1A2 transporter
Bibliographic record
Abstract
Background OATP1A2 is a membrane transporter potentially involved in the absorption of various drugs. Previous data demonstrated that the uptake of rosuvastatin through OATP1A2 can be inhibited by several β‐blockers, where carvedilol is the most potent inhibitor. Carvedilol structurally differs from the other β‐blockers tested by its tricyclic moiety. The goal of this study was to determine whether the tricyclic structure of carvedilol is responsible for its strong inhibitory effect on OATP1A2. Methods A HEK293 cell line overexpressing OATP1A2 was used as model. They were co‐incubated in the presence of rosuvastatin and increasing concentrations of different tricyclic compounds. The amount of rosuvastatin transported in the cells was measured by HPLC. Results Most tricyclic compounds evaluated inhibited rosuvastatin uptake through OATP1A2 with different IC 50 . Our data show that the inhibition is competitive. Compound IC 50 (μM) Compound IC 50 (μM) carazolol 4.0 nortriptyline 14.8 amitriptyline 5.0 chlorpromazine 29.6 imipramine 12.6 desipramine 77.9 trimipramine 13.6 carbamazepine >;100 doxepin 14.0 carbazole No effect clomipramine 14.7 phenothiazine No effect Conclusions The inhibitory component is made up of the tricyclic ring with a short aliphatic chain. Consequently, drugs with a similar structure may strongly modulate the transport of OATP1A2 substrates. Funding: CIHR, FRSQ, Foundation CHUM
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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) | 0.003 | 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".