Probing the Formation Kinetics and Thermodynamics with Rationally Designed Analytical Tools Enables One-Pot Synthesis and Purification of a Tetrahedral DNA Nanostructure
Bibliographic record
Abstract
The development of robust analytical tools capable of probing the formation kinetics and thermodynamics of DNA nanostructures is a crucial step toward better understanding and manufacturing of diverse DNA-based materials. Herein, we introduce a real-time fluorescence anisotropy assay and rationally designed DNA reaction termination probes (DRTPs) as a set of new tools for exploring the formation mechanisms of DNA nanostructures. We deployed these tools for probing the formation of a classic tetrahedral DNA nanostructure (TDN) as a model system. Our tools revealed that the formation of TDN was dominated by simultaneous hybridization, whereas its undesired side products were caused mainly through step-wise hybridization. An optimal reaction temperature exists that favors the formation of TDN over side products. With insight into the TDN formation mechanism, we further engineered magnetic DRTPs to achieve single-step purification of TDN, enabling 10-fold improvement in the ratio between the targeted TDN and undesired side products without tedious procedures or bulky instruments. Combining the optimal reaction and purification conditions, we finally demonstrated the one-pot synthesis and purification of TDN. The analytical techniques offered in this work may hold potential to find wide applications and inspire new analytical methods for structural DNA nanotechnology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".