Unveiling the Distinct Mechanisms by which Disease-Causing Mutations in the Kelch Domain of KLHL3 Disrupt the Interaction with the Acidic Motif of WNK4 through Molecular Dynamics Simulation
Bibliographic record
Abstract
Kelch-like 3 (KLHL3) is a substrate adaptor of an E3 ubiquitin ligase complex that regulates the degradation of its substrates, including with-no-lysine [K] kinase 4 (WNK4). Mutations in KLHL3 are associated with pseudohypoaldosteronism type II (PHAII), a hereditary form of hypertension. Many PHAII-causing mutations are located in the Kelch domain of KLHL3 that binds with WNK4; however, detailed mechanisms by which these mutations disrupt the binding are not well-understood. In the present study we use molecular dynamics simulations and Western blot analyses to examine the effects of these mutations on the interaction between the Kelch domain of KLHL3 and the acidic motif (AM) of WNK4. The simulation results correlated well with those from Western blot analyses with the exception of the L387P mutation, which led to deregulation of AM degradation by KLHL3 but not recapitulated by simulations. On the basis of the simulation results, a mutation on the binding surface of the Kelch domain affected the Kelch-AM interaction through two major mechanisms: altering the electrostatic potential of the AM binding site and disrupting the Kelch-AM hydrogen bonds. The mutations buried inside the Kelch domain were predicted by our simulations to have no or modest effects on the Kelch-AM interaction. Buried mutations R384Q and S410L disrupted intramolecular hydrogen bonds within the Kelch domain and affected the Kelch-AM interaction indirectly. No significant effect of buried mutation A340V or A494T on the AM degradation or Kelch-AM interaction was observed, implying these mutations may disrupt mechanisms other than Kelch-AM interaction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".