Role of catechins on ET-1-induced stimulation of PLD and NADPH oxidase activities in pulmonary smooth muscle cells: determination of the probable mechanism by molecular docking studies
Bibliographic record
Abstract
The treatment of human pulmonary artery smooth muscle cells with ET-1 stimulates the activity of PLD and NADPH oxidase, but this stimulation is inhibited by pretreatment with bosentan (ET-1 receptor antagonist), FIPI (PLD inhibitor), apocynin (NADPH oxidase inhibitor), and EGCG and ECG (catechins having a galloyl group), but not EGC and EC (catechins devoid of a galloyl group). Herein, using molecular docking analyses based on our biochemical studies, we determined the probable mechanism by which the catechins containing a galloyl group inhibit the stimulation of PLD activity induced by ET-1. The ET-1-induced stimulation of PLD activity was inhibited by SecinH3 (inhibitor of cytohesin). Arf6 and cytohesin-1 are associated in the cell membrane, which is not inhibited by the catechins during ET-1 treatment of the cells. However, EGCG and ECG inhibited the binding of GTPγS with Arf6, even in the presence of cytohesin-1. The molecular docking analyses revealed that the catechins containing a galloyl group (EGCG and ECG) with cytohesin-1–Arf6GDP, but not the catechins without a galloyl group (EGC and EC), prevent GDP–GTP exchange in Arf6, which seems to be an important mechanism for inhibiting the activation of PLD induced by ET-1, and subsequently increases the activity of NADPH oxidase.
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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) | 0.001 | 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".