RNA G-Quadruplex Reprogramming with Guanine-Rich Antisense Oligonucleotides Inhibits Monoamine Oxidase B’s Translation
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The human transcriptome contains secondary RNA structures like RNA G-quadruplexes (rG4s) which regulate biological processes such as translation by ribosome stalling. Canonical rG4s, which are stabilized by both Hoogsteen hydrogen bonds and potassium ions, are known to hinder translation in the 5′ untranslated region (5′UTR) of mRNAs. In neurodegenerative diseases, including Parkinson’s disease (PD), rG4s have been shown to influence protein synthesis. However, the impact of rG4s in nonmutated therapeutic targets like monoamine oxidase B (MAOB), an enzyme involved in dopamine metabolism, remains unexplored. In this study, an rG4 located in the MAOB mRNA’s 5′UTR was identified, and ways to either stabilize or reprogram this rG4 were explored. The translation inhibitory role of the rG4 was demonstrated both in vitro and in cellulo and was shown to be further accentuated in the presence of the PhenDC3 ligand. As an alternative to ligands, which cannot specifically stabilize only one G4, the MOAB rG4 was reprogrammed with G-rich antisense oligonucleotides (G-ASOs) from a two-quartets to three-quartets G4. The G-ASOs, either unmodified DNA or 2′OMe, were shown to both induce a new rG4 folding through intermolecular interactions and to specifically reduce the translation of MAOB both in vitro and in cellulo . These findings propose a targeted approach with which to modulate rG4 structures for therapeutics, suggesting that rG4 folding, when stabilized by G-ASOs, could regulate protein synthesis and even potentially alleviate PD symptoms by reducing MAOB activity. This approach opens new avenues as it could be used to reduce the expression of many therapeutic protein targets.
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 | 0.001 |
| 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".