Synthesis and Preliminary Evaluation of an ASGPr-Targeted Polycationic β-Cyclodextrin Carrier for Nucleosides and Nucleotides
Bibliographic record
Abstract
Most antiviral and anticancer nucleosides are prodrugs that require stepwise phosphorylation to their triphosphate nucleotide form for biological activity. Monophosphorylation may be rate-limiting, and the nucleotides may be unstable and poorly internalized by target cells. Effective targeting and delivery systems for nucleoside drugs, including oligonucleotides used in molecular therapeutics, could augment their efficacy. The development of a carrier designed to effect selective transmembrane internalization of nucleotides via the asialoglycoprotein receptor (ASGPr) is now reported. In this work, the polycationic, polygalactosyl drug delivery carrier heptakis[6-amino-6-deoxy-2-O-(3-(1-thio-β-D-galactopyranosyl)-propyl)]-β-cyclodextrin hepta-acetate salt (GCyDAc), potentially a bifunctional carrier of (poly)nucleotides, was modeled by molecular docking in silico as an ASGPr-ligand, then synthesized for testing. The antivirals arabinosyl adenine (araA, vidarabine, an early generation antiviral nucleoside), arabinosyl adenine 5′-monophosphate (araAMP), and 12-mer-araAMP (p-araAMP) were selected for individual formulation with GCyDAc to develop this concept. Experimentally, beta cyclodextrin was decorated with seven protonated amino substituents on the primary face, and seven thiogalactose residues on its secondary face. AraA, araAMP, and p-araAMP were individually complexed with GCyDAc and complex formation for each drug was confirmed by differential scanning calorimetry (DSC). Finally, the free drugs and their GCyDAc complexes were evaluated for antiviral activity using ASGPr-expressing HepAD38 cells in cell culture. In this model, araA, araAMP, and p-araAMP showed relative antiviral potencies of 1.0, 1.1, and 1.2, respectively. In comparison, GCyDAc-complexes of araA, araAMP, and p-araAMP were 2.5, 1.3, and 1.2 times more effective than non-complexed araA in suppressing viral DNA production. The antiviral potencies of these complexes were minimally supportive of the hypothesis that ASGPr-targeted, CyD-based charge-association complexation of nucleosides and nucleotides could effectively enhance antiviral efficacy. GCyDAc was non-toxic to mammalian cells in cell culture, as determined using the MTS proliferation assay.
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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) | 0.000 | 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".