Conformation and dynamics of the kinase domain drive subcellular location and activation of LRRK2
Bibliographic record
Abstract
To explore how pathogenic mutations of the multidomain leucine-rich repeat kinase 2 (LRRK2) hijack its finely tuned activation process and drive Parkinson’s disease (PD), we used a multitiered approach. Most mutations mimic Rab-mediated activation by “unleashing” kinase activity, and many, like the kinase inhibitor MLi-2, trap LRRK2 onto microtubules. Here we mimic activation by simply deleting the inhibitory N-terminal domains and then characterize conformational changes induced by MLi-2 and PD mutations. After confirming that LRRK2 RCKW retains full kinase activity, we used hydrogen-deuterium exchange mass spectrometry to capture breathing dynamics in the presence and absence of MLi-2. Solvent-accessible regions throughout the entire protein are reduced by MLi-2 binding. With molecular dynamics simulations, we created a dynamic portrait of LRRK2 RCKW and demonstrate the consequences of kinase domain mutations. Although all domains contribute to regulating kinase activity, the kinase domain, driven by the DYGψ motif, is the allosteric hub that drives LRRK2 regulation.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".