Sequence-function relationships provide new insight into the cleavage site selectivity of the 8-17 RNA-cleaving deoxyribozyme
Bibliographic record
Abstract
Many sequence variations of the 8-17 RNA-cleaving deoxyribozyme have been isolated through in vitro selection. In an effort to understand how these sequence variations affect cleavage site selectivity, we systematically mutated the catalytic core of 8-17 and measured the cleavage activity of each mutant deoxyribozyme against all 16 possible chimeric (RNA/DNA) dinucleotide junctions. We observed sequence-function relationships that suggest how the following non-conserved positions in the catalytic core influence selectivity at the dinucleotide (5' rN(18)-N(1.1) 3') cleavage site: (i) positions 2.1 and 12 represent a primary determinant of the selectivity at the 3' position (N(1.1)) of the cleavage site; (ii) positions 15 and 15.0 represent a primary determinant of the selectivity at the 5' position (rN(18)) of the cleavage site and (iii) the sequence of the 3-bp intramolecular stem has relatively little influence on cleavage site selectivity. Furthermore, we report for the first time that 8-17 variants have the collective ability to cleave all dinucleotide junctions with rate enhancements of at least 1000-fold over background. Three optimal 8-17 variants, identified from approximately 75 different sequences that were examined, can collectively cleave 10 of 16 junctions with useful rates of >/=0.1 min(-1), and exhibit an overall hierarchy of reactivity towards groups of related junctions according to the order NG > NA > NC > NT.
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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 | 0.001 |
| 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".