Toward the Establishment of a Harmonized Physicochemical Profiling Platform for Therapeutic Oligonucleotides: A Case Study for Aptamers Where the Higher-Order Structure Influences Physical Properties
Bibliographic record
Abstract
Oligonucleotides are short nucleic acids that serve as one of the most promising classes of drug modality. However, attempts to establish a physicochemical evaluation platform of oligonucleotides for acquiring a comprehensive view of their properties have been limited. As the chemical stability and the efficacy as well as the solution properties at a high concentration should be related to their higher-order structure and intra-/intermolecular interactions, their detailed understanding enables effective formulation development. Here, the higher-order structure and the thermodynamic stability of the thrombin-binding aptamer (TBA) and four modified TBAs, which have similar sequences but were expected to have different higher-order structures, were evaluated using ultraviolet spectroscopy (UV), circular dichroism (CD), differential scanning calorimetry (DSC), and nuclear magnetic resonance (NMR). Then, the relationship between the higher-order structure and the solution properties including solubility, viscosity, and stability was investigated. The impact of the higher-order structure on the antithrombin activity was also confirmed. The higher-order structure and intra-/intermolecular interactions of the oligonucleotides were affected by types of buffers because of different potassium concentrations, which are crucial for the formation of the G-quadruplex structure. Consequently, solution properties, such as solubility and viscosity, chemical stability, and antithrombin activity, were also influenced. Each instrumental analysis had a complemental role in investigating the higher-order structure of TBA and modified TBAs. The utility of each physicochemical characterization method during the preclinical developmental stages is also discussed.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".