Targeting α-synuclein oligomers: The importance of characterisation
Bibliographic record
Abstract
Parkinson’s Disease (PD) is a complex disease, characterised by degeneration of neocortical, limbic and nigrostriatal neurons. It is unknown what initiates neurodegeneration, but soluble oligomers of the protein α-synuclein (αSn) seem to be particularly toxic, compared to insoluble fibrils. Although there is currently no cure for PD, αSn oligomers (αSOs) are a potential therapeutic target, but a major drawback it that little is known about the nature of PD-associated αSOs. The scientific literature describes a wide variety of protocols to generate αSOs in vitro, with a subsequent heterogeneity in reported structure and bioactivities, making it difficult to predict which species is/are most relevant. The aim of this thesis is to improve and expand current knowledge on αSOs and their role in PD, with a focus on αSOs modified by the polyunsaturated fatty acid docosahexaenoic acid (DHA), and the reactive aldehyde 4-hydroxynonenal (HNE), on which current literature is limited. We performed extended characterisation using techniques aimed at resolving morphological, structural, chemical, dynamical and functional properties. We showed that, despite their clear chemical differences, DHA- and HNE-αSOs share a remarkable amount of resemblance with unmodified αSOs: they were spherical, had an anti-parallel β-sheet character, were most protected from hydrogen/deuterium exchange in the core region of αSn, and were able to permeabilize small synthetic vesicles. Nonetheless, both species also had their own unique characteristics, e.g. they were recognized by different conformational antibodies and DHA–αSOs also formed a second elongated species in addition to the dominant spherical species. Although further functional testing is needed, this suggests that each species has its own distinct toxic mechanism, in addition to what may be a shared common contribution to pathology. Finally we showed that both species co-localised with glutamatergic synapses of hippocampal neurons upon addition to the cell culture medium, and we identified six proteins which might explain this synaptic binding of DHA-αSOs: VAMP-2B, Na+/K+ ATPase, V-type ATPase, VDAC, CaMKII and Rab-3A. The identification of these targets is a first step towards unravelling the toxic pathways which are activated upon synaptic binding of extracellularly added αSOs, and hopefully will contribute to the discovery of new disease modifying compounds, which can block the toxic interaction between the αSOs and their binding partner.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".