Site and Mechanism of ML252 Inhibition of Kv7 Voltage-Gated Potassium Channels
Bibliographic record
Abstract
Kv7 (KCNQ) voltage-gated potassium channels are critical regulators of neuronal excitability and are candidate targets for development of antiseizure medications. Drug discovery efforts have identified small molecules that modulate channel function and reveal mechanistic insights into Kv7 channel physiological roles. While Kv7 channel activators have therapeutic benefits, inhibitors are useful for understanding channel function and mechanistic validation of candidate drugs. In this study, we reveal the mechanism of a Kv7.2/Kv7.3 inhibitor, ML252. We used docking and electrophysiology to identify critical residues involved in ML252 sensitivity. Most notably, Kv7.2[W236F] or Kv7.3[W265F] mutations strongly attenuate ML252 sensitivity. This tryptophan residue in the pore is also required for sensitivity to certain activators, including retigabine and ML213. We used automated planar patch clamp electrophysiology to assess competitive interactions between ML252 and different Kv7 activator subtypes. A pore-targeted activator (ML213) weakens the inhibitory effects of ML252, whereas a distinct activator subtype (ICA-069673) that targets the voltage sensor does not prevent ML252 inhibition. Using transgenic zebrafish larvae expressing an optical reporter (CaMPARI) to measure neural activity in-vivo, we demonstrate that Kv7 inhibition by ML252 increases neuronal excitability. Consistent with in-vitro data, ML213 suppresses ML252 induced neuronal activity, while the voltage-sensor targeted activator ICA-069673 does not prevent ML252 actions. In summary, this study establishes a binding site and mechanism of action of ML252, classifying this poorly understood drug as a pore-targeted Kv7 channel inhibitor that binds to the same tryptophan residue as commonly used pore-targeted Kv7 activators. ML213 and ML252 likely have overlapping sites of interaction in the pore Kv7.2 and Kv7.3 channels, resulting in competitive interactions. In contrast, the VSD-targeted activator ICA-069673 does not prevent channel inhibition by ML252.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".