Heme activation by DNA: isoguanine pentaplexes, but not quadruplexes, bind heme and enhance its oxidative activity
Bibliographic record
Abstract
Guanine-rich, single-stranded, DNAs and RNAs are able to fold to form G-quadruplexes that are held together by guanine base quartets. G-quadruplexes are known to bind ferric heme [Fe(III)-protoporphyrin IX] and to strongly activate such bound hemes toward peroxidase (1-electron oxidation) as well as oxygenase/peroxygenase (2-electron oxidation) activities. However, much remains unknown about how such activation is effected. Herein, we investigated whether G-quadruplexes were strictly required for heme activation or whether related multi-stranded DNA/RNA structures such as isoguanine (iG) quadruplexes and pentaplexes could also bind and activate heme. We found that iG-pentaplexes did indeed bind and activate heme comparably to G-quadruplexes; however, iG-quadruplexes did neither. Earlier structural and computational studies had suggested that while the geometry of backbone-unconstrained iG-quintets templated by cations such as Na(+) or NH4 (+) was planar, that of iG-quartets deviated from planarity. We hypothesize that the binding as well as activation of heme by DNA or RNA is strongly supported by the planarity of the nucleobase quartet or quintet that interacts directly with the heme.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".