DNA–Protein Noncovalent Cross‐Linking: Ruthenium Dipyridophenazine Biotin Complex for the Assembly of Proteins and Gold Nanoparticles on DNA Templates
Bibliographic record
Abstract
We report the first example of a small molecule that can noncovalently cross-link DNA with streptavidin and streptavidin-labeled materials. Molecule 1 possesses a ruthenium dipyridophenazine DNA-intercalating moiety and a biotin unit; these two units are adequately separated to ensure efficient cross-linking of DNA with protein. Complex 1 is essentially nonemissive in aqueous solution and when bound to streptavidin, however, its luminescence is turned "on" when it binds to DNA. We have used these properties to establish that this complex can simultaneously bind to DNA and streptavidin, and can thus bring these two biomolecules together. We also synthesized a related molecule, 3, in which the biotin and DNA-intercalating moieties are covalently bound. While complex 3 can intercalate into DNA through a threading mechanism, luminescence experiments show that it cannot simultaneously bind DNA and streptavidin, most likely due to the proximity of its two molecular-recognition units. The cross-linking ability of molecule 1 was used to template the assembly of streptavidin molecules on circular plasmid DNA, as visualized by atomic force microscopy. In addition, using 1, we show the organization of discrete groups of gold nanoparticles labeled with streptavidin on a linear DNA template of finite size, with transmission electron microscopy. In these experiments the DNA template acted as a "molecular ruler" that dictated the number of particles in the assembly.
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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 | 0.001 | 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".