Structurally constrained phosphonate internucleotide linkage impacts oligonucleotide-enzyme interaction, and modulates siRNA activity and allele specificity
Bibliographic record
Abstract
Oligonucleotides is an emerging class of chemically-distinct therapeutic modalities, where extensive chemical modifications are fundamental for their clinical applications. Inter-nucleotide backbones are critical to the behaviour of therapeutic oligonucleotides, but clinically explored backbone analogues are, effectively, limited to phosphorothioates. Here, we describe the synthesis and bio-functional characterization of an internucleotide (E)-vinylphosphonate (iE-VP) backbone, where bridging oxygen is substituted with carbon in a locked stereo-conformation. After optimizing synthetic pathways for iE-VP-linked dimer phosphoramidites in different sugar contexts, we systematically evaluated the impact of the iE-VP backbone on oligonucleotide interactions with a variety of cellular proteins. Furthermore, we systematically evaluated the impact of iE-VP on RNA-Induced Silencing Complex (RISC) activity, where backbone stereo-constraining has profound position-specific effects. Using Huntingtin (HTT) gene causative of Huntington's disease as an example, iE-VP at position 6 significantly enhanced the single mismatch discrimination ability of the RISC without negative impact on silencing of targeting wild type htt gene. These findings suggest that the iE-VP backbone can be used to modulate the activity and specificity of RISC. Our study provides (i) a new chemical tool to alter oligonucleotide-enzyme interactions and metabolic stability, (ii) insight into RISC dynamics and (iii) a new strategy for highly selective SNP-discriminating siRNAs.
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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 | 0.000 | 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".