A bimolecular modification strategy for developing long-lasting bone anabolic aptamer
Bibliographic record
Abstract
The molecular weight of nucleic acid aptamers (20 kDa) is lower than the cutoff threshold of the renal filtration (30-50 kDa), resulting in a very short half-life, which dramatically limits their druggability. To address this, we utilized 3-(2,5-dioxo-2,5-dihydro-1H-pyrrol-1-yl)-N-(4-hydroxy-2-oxo-2H-chromen-6-yl)propenamide (HC) and 12-((2,5-dioxopyrrolidin-1-yl)oxy)-12-oxododecanoic acid (DA), two newly designed coupling agents, for synergistic binding to human serum albumin (HSA). Both HC and DA are conjugated to a bone anabolic aptamer (Apc001) against sclerostin to form an Apc001OC conjugate with high binding affinity to HSA. Notably, HC and DA could synergistically facilitate prolonging the half-life of the conjugated Apc001 and promoting its bone anabolic potential. Using the designed blocking peptides, the mechanism studies indicate that the synergistic effect of HC-DA on pharmacokinetics and bone anabolic potential of the conjugated Apc001 is achieved via their synergistic binding to HSA. Moreover, biweekly Apc001OC at 50 mg/kg shows comparable bone anabolic potential to the marketed sclerostin antibody given weekly at 25 mg/kg. This proposed bimolecular modification strategy could help address the druggability challenge for aptamers with a short half-life.
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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".