The Niemann-Pick C1 Inhibitor NP3.47 Enhances Gene Silencing Potency of Lipid Nanoparticles Containing siRNA
Bibliographic record
Abstract
The therapeutic applications of lipid nanoparticle (LNP) formulations of small interfering RNA (siRNA), are hampered by inefficient delivery of encapsulated siRNA to the cytoplasm following endocytosis. Recent work has shown that up to 70% of endocytosed LNP-siRNA particles are recycled to the extracellular medium and thus cannot contribute to gene silencing. Niemann-Pick type C1 (NPC1) is a late endosomal/lysosomal membrane protein required for efficient extracellular recycling of endosomal contents. Here we assess the influence of NP3.47, a putative small molecule inhibitor of NPC1, on the gene silencing potency of LNP-siRNA systems in vitro. Intracellular uptake and colocalization studies revealed that the presence of NP3.47 caused threefold or higher increases in accumulation of LNP-siRNA in late endosomes/lysosomes as compared with controls in a variety of cell lines. The gene silencing potency of LNP siRNA was enhanced up to fourfold in the presence of NP3.47. Mechanisms of action studies are consistent with the proposal that NP3.47 acts to inhibit NPC1. Our findings suggest that the pharmacological inhibition of NPC1 is an attractive strategy to enhance the therapeutic efficacy of LNP-siRNA by trapping LNP-siRNA in late endosomes, thereby increasing opportunities for endosomal escape.
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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 | 0.001 |
| 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".