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Record W4412110230 · doi:10.1080/15548627.2025.2531025

Activation of endogenous PRKN by structural derepression is linked to increased turnover of the E3 ubiquitin ligase

2025· article· en· W4412110230 on OpenAlexafffund
Fabienne C. Fiesel, Bernardo A. Bustillos, Jens O. Watzlawik, Carol Chen, Martin H. Berryer, Jiazhen Zhang, Paige K Boneski, Caleb Hayes, Jenny Bredenberg, Éric Deneault, Zhipeng You, Narges Abdien, Nathalia Aprahamian, Taylor Goldsmith, Zahra Baninameh, Liam T. Cocker, Haonan Zhang, Matthew S. Goldberg, Edward A. Fon, Jean‐François Trempe, Satpal Virdee, Thomas M. Durcan, Wolfdieter Springer

Bibliographic record

VenueAutophagy · 2025
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsOntario Brain InstituteMcGill University Health CentreStructural Genomics ConsortiumMcGill UniversityHealth CanadaMontreal Neurological Institute and Hospital
FundersRobert and Arlene Kogod Center on AgingCongressionally Directed Medical Research ProgramsNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchNational Institutes of HealthUniversity of DundeeTed Nash Long Life FoundationFlorida Department of HealthMichael J. Fox Foundation for Parkinson's ResearchU.S. Department of Defense
KeywordsMitophagyBiologyUbiquitin ligaseUbiquitinPINK1AutophagyCell biologyDerepressionMitochondrionDeubiquitinating enzymeBiochemistryGenePsychological repressionApoptosis

Abstract

fetched live from OpenAlex

Loss-of-function mutations in the PINK1 and PRKN genes are the most common cause of early-onset Parkinson disease (PD). The encoded enzymatic pair selectively identifies, labels, and targets damaged mitochondria for degradation via the macroautophagy/autophagy-lysosome system (mitophagy). This pathway is cytoprotective and efforts to activate mitophagy are pursued as therapeutic avenues to combat PD and other neurodegenerative disorders. When mitochondria are damaged, the ubiquitin kinase PINK1 accumulates and recruits PRKN from the cytosol to activate the E3 ubiquitin ligase from its auto-inhibited conformation. We have previously designed several mutations that effectively derepress the structure of PRKN and activate its enzymatic functions in vitro. However, it remained unclear how these PRKN-activating mutations would perform endogenously in cultured neurons or in vivo in the brain. Here, we gene-edited neural progenitor cells and induced pluripotent stem cells to express PRKN-activating mutations in dopaminergic cultures. All tested PRKN-activating mutations indeed enhanced the enzymatic activity of PRKN in the absence of exogenous stress, but their hyperactivity was linked to their own PINK1-dependent degradation. Strikingly, in vivo in a mouse model expressing an equivalent activating mutation, we find the same relationship between PRKN enzymatic activity and protein stability. We conclude that PRKN degradation is the consequence of its structural derepression and enzymatic activation, thus resulting only in a temporary gain of activity. Our findings imply that pharmacological activation of endogenous PRKN will lead to increased turnover and suggest that additional considerations might be necessary to achieve sustained E3 ubiquitin ligase activity for disease treatment.Abbreviations: BSA: bovine serum album, CCCP: carbonyl cyanide 3-chlorophenylhydrazone; ECL: electrochemiluminescence; EGF: epidermal growth factor; ELISA: enzyme-linked immunosorbent assay; FGF: fibroblast growth factor; iPSC: induced pluripotent stem cell; KI: knock-in; KO: knockout; MAP2: microtubule associated protein 2; MFN2: mitofusin 2; MSD: Meso Scale Discovery; mt-Keima: mitochondrial targeted Keima; NPC: neural progenitor cell; PD: Parkinson disease; PDH: pyruvate dehydrogenase; p-S65-PRKN: Serine 65 phosphorylated PRKN; p-S65-Ub: Serine 65 phosphorylated ubiquitin; REP: repressor element of PRKN; TH: tyrosine hydroxylase; TX: Triton X-100, Ub: ubiquitin; UBL: ubiquitin-like; WT: wild-type.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.283
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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