Exploring the role of post‐translational modifications in regulating α‐synuclein interactions by studying the effects of phosphorylation on nanobody binding
Bibliographic record
Abstract
Intracellular deposits of α-synuclein in the form of Lewy bodies are major hallmarks of Parkinson's disease (PD) and a range of related neurodegenerative disorders. Post-translational modifications (PTMs) of α-synuclein are increasingly thought to be major modulators of its structure, function, degradation and toxicity. Among these PTMs, phosphorylation near the C-terminus at S129 has emerged as a dominant pathogenic modification as it is consistently observed to occur within the brain and cerebrospinal fluid (CSF) of post-mortem PD patients, and its level appears to correlate with disease progression. Phosphorylation at the neighboring tyrosine residue Y125 has also been shown to protect against α-synuclein toxicity in a Drosophila model of PD. In the present study we address the potential roles of C-terminal phosphorylation in modulating the interaction of α-synuclein with other protein partners, using a single domain antibody fragment (NbSyn87) that binds to the C-terminal region of α-synuclein with nanomolar affinity. The results reveal that phosphorylation at S129 has negligible effect on the binding affinity of NbSyn87 to α-synuclein while phosphorylation at Y125, only four residues away, decreases the binding affinity by a factor of 400. These findings show that, despite the fact that α-synuclein is intrinsically disordered in solution, selective phosphorylation can modulate significantly its interactions with other molecules and suggest how this particular form of modification could play a key role in regulating the normal and aberrant function of α-synuclein.
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".