Structure-based design and characterization of Parkin activating mutations
Bibliographic record
Abstract
Abstract Human autosomal recessive mutations in the Parkin gene are causal for Parkinson’s disease (PD). Parkin encodes a ubiquitin E3 ligase that functions together with the PD associated kinase, PINK1, in a mitochondrial quality control pathway. Structural studies reveal that Parkin exists in an inactive conformation mediated by multiple autoinhibitory domain interfaces. Here we have performed comprehensive mutational analysis of both human and rat Parkin to unbiasedly determine Parkin activating mutations across all major autoinhibitory interfaces. Out of 31 mutations tested, we identify 11 activating mutations clustered near the RING0:RING2 or REP:RING1 interfaces, which reduce the thermal stability of Parkin. Of these, we demonstrate that three mutations, V393D, A401D, and W403A located at the REP:RING1 interface were able to completely rescue a Parkin S65A mutant, defective in mitophagy, in cell-based studies. Overall our data extends previous analysis of Parkin activation mutants and suggests that small molecules that mimic REP:RING1 destabilisation offer therapeutic potential for PD patients harbouring select Parkin mutations. Summary blurb Parkin, an E3 ubiquitin ligase involved in Parkinson’s disease, is inactive in the basal state and is activated by PINK1 to mediate mitophagy. Here we characterized 31 mutations and discovered three that activate Parkin and rescue loss of PINK1 phosphorylation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".