Dual effects of mefenamic acid on the <i>I</i><sub>Ks</sub> molecular complex
Bibliographic record
Abstract
Abstract Background and Purpose Mutations in both KCNQ1 and KCNE1, which together form the cardiac IKs current, are associated with inherited conditions such as long and short QT syndromes. Mefenamic acid, a non‐steroidal anti‐inflammatory drug, is an IKs potentiator and may be utilised as an archetype to design therapeutically useful IKs agonists. However, here we show that mefenamic acid can also act as an IKs inhibitor, and our data reveal its dual effects on KCNQ1/KCNE1 channels. Experimental Approach Effects of mefenamic acid on wild type (WT) and mutant KCNQ1/KCNE1 channels expressed in tsA201 cells were studied using whole cell patch clamp. Molecular dynamics simulations were used to determine trajectory clustering. Key Results Mefenamic acid inhibits WT IKs at high concentrations while preserving some attributes of current potentiation. Inhibitory actions of mefenamic acid are unmasked at lower drug concentrations by KCNE1 and KCNQ1 mutations in the mefenamic acid binding pocket, at the extracellular end of KCNE1 and in the KCNQ1 S6 helix. Mefenamic acid does not inhibit KCNQ1 in the absence of KCNE1 but inhibits IKs current in a concentration‐dependent manner in the mutant channels. Inhibition involves modulation of pore kinetics and/or voltage sensor domain‐pore coupling in WT and in the KCNE1 E43C mutant. Conclusion and Implications This work highlights the importance of structural motifs at the extracellular inter‐subunit interface of KCNQ1 and KCNE1 channels, and their interactions, in determining the nature of drug effects on the IKs channel complex and has important implications for treating patients with specific long QT mutations.
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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 | 0.000 |
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".