A Robust Strategy for Introducing Amino‐Modifiers in Nucleic Acids: Enabling Novel Amino Tandem Oligonucleotide Synthesis in DNA and RNA
Bibliographic record
Abstract
Amino-modifiers are pivotal chemical modifications in nucleic acid scaffolds, serving applications ranging from (bio)conjugation to probing the origins of life. We report a simple, efficient, and cost-effective methodology for the introduction of amino-modifiers into DNA and RNA. This approach leverages a commercially available sulfonyl-containing solid support, which is first converted into a mixed N-hydroxysuccinimide carbonate, enabling robust conjugation with primary and secondary amines whether nucleosidic or non-nucleosidic. Oligonucleotides are synthesized via solid-phase synthesis and purified using standard methods, with little to no modification. Building on this framework, we introduce a novel amino-containing tandem oligonucleotide synthesis (aTOS) methodology, which facilitates the introduction of multiple terminal amino (or monophosphate) groups across two oligonucleotide strands. This innovative method broadens the toolkit for the introduction of amino modifications in nucleic acids, for applications in nucleic acid (bio)chemistry and biotechnology.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".