Selective localization of Mfn2 near PINK1 enable its preferential ubiquitination by Parkin on mitochondria
Bibliographic record
Abstract
Abstract Mutations in Parkin and PINK1 cause an early-onset familial Parkinson’s disease. Parkin is a RING-In-Between-RING (RBR) E3 ligase that transfers ubiquitin from an E2 enzyme to a substrate in two steps: 1) thioester intermediate formation on Parkin, and 2) acyl transfer to a substrate lysine. The process is triggered by PINK1, which phosphorylates ubiquitin on damaged mitochondria, which in turn recruits and activates Parkin. This leads to the ubiquitination of outer mitochondrial membrane proteins and clearance of the organelle. While the targets of Parkin on mitochondria are known, the factors determining substrate selectivity remain unclear. To investigate this, we examined how Parkin catalyzes ubiquitin transfer to substrates. We found that His433 in the RING2 domain catalyzes acyl transfer. In cells, mutation of His433 impairs mitophagy. In vitro ubiquitination assays with isolated mitochondria show that Mfn2 is a kinetically preferred substrate. Using proximity-ligation assays, we show that Mfn2 specifically co-localizes with PINK1 and phospho-ubiquitin in U2OS cells upon mitochondrial depolarization. We propose a model whereby ubiquitination of Mfn2 is efficient by virtue of its localization near PINK1, which leads to the recruitment and activation of Parkin via phospho-ubiquitin at these sites.
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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 | 0.001 |
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".