Crystal Structures of the Mango-II RNA Aptamer Reveal Heterogeneous Fluorophore Binding and Guide Engineering of Variants with Improved Selectivity and Brightness
Bibliographic record
Abstract
Several RNA aptamers that bind small molecules and enhance their fluorescence have been successfully used to tag and track RNAs in vivo, but these genetically encodable tags have not yet achieved single-fluorophore resolution. Recently, Mango-II, an RNA that binds TO1-Biotin with ∼1 nM affinity and enhances its fluorescence by >1500-fold, was isolated by fluorescence selection from the pool that yielded the original RNA Mango. We determined the crystal structures of Mango-II in complex with two fluorophores, TO1-Biotin and TO3-Biotin, and found that despite their high affinity, the ligands adopt multiple distinct conformations, indicative of a binding pocket with modest stereoselectivity. Mutational analysis of the binding site led to Mango-II(A22U), which retains high affinity for TO1-Biotin but now discriminates >5-fold against TO3-biotin. Moreover, fluorescence enhancement of TO1-Biotin increases by 18%, while that of TO3-Biotin decreases by 25%. Crystallographic, spectroscopic, and analogue studies show that the A22U mutation improves conformational homogeneity and shape complementarity of the fluorophore-RNA interface. Our work demonstrates that even after extensive functional selection, aptamer RNAs can be further improved through structure-guided engineering.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".