Identification and structural characterization of small molecule inhibitors of PINK1
Bibliographic record
Abstract
Abstract Mutations in PINK1 and Parkin cause early-onset Parkinson’s Disease (PD). PINK1 is a kinase which functions as a mitochondrial damage sensor and initiates mitochondrial quality control by accumulating on the damaged organelle. There, it phosphorylates ubiquitin, which in turn recruits and activates Parkin, an E3 ubiquitin ligase. Ubiquitylation of mitochondrial proteins leads to the autophagic degradation of the damaged organelle. Pharmacological modulation of PINK1 constitutes an appealing avenue to study its physiological function and develop therapeutics. In this study, we used a thermal shift assay with insect PINK1 to identify small molecules that inhibit ATP hydrolysis and ubiquitin phosphorylation. PRT062607, an SYK inhibitor, is the most potent inhibitor in our screen and inhibits both insect and human PINK1, with an IC 50 in the 0.5–3 µM range in HeLa cells and dopaminergic neurons. The crystal structures of insect PINK1 bound to PRT062607 or CYC116 reveal how the compounds interact with the ATP-binding pocket. PRT062607 notably engages with the catalytic aspartate and causes a destabilization of insert-2 at the autophosphorylation dimer interface. While PRT062607 is not selective for PINK1, it provides a scaffold for the development of more selective and potent inhibitors of PINK1 that could be used as chemical probes.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".