Electronic Energy Changes Associated with Guanine Quadruplex Formation: An Investigation at the Atomic Level
Bibliographic record
Abstract
Guanine quadruplexes have received a lot of attention due to their possible role as therapeutic agents. Specifically, it is the ability of these quadruplex structures to inhibit telomerase, an enzyme found to be highly active in a large percentage of tumor cells and thought to confer immortality upon these cells. However, although a great deal of research has focused on enhancing the formation of these structures and their anticancer activity, many questions remain about the quadruplex structures themselves. The current study probes the nature of these quadruplex structures at the atomic level. Individual atomic energies have been computed for the quadruplex structure and compared to the atomic energies of the unfolded telomere to determine the energetic consequences of quadruplex formation. The results suggest several interesting trends, most notably that the guanine quartets exhibit an alternating pattern of stabilization and destabilization and these regions actually overlap in the intact quadruplex. In addition, the TTA loop segments are largely stabilized, whereas the atoms in the sugar-phosphate backbone exhibit mostly minor changes going from the unfolded to folded state. Inclusion of additional sodium cations in the central core of the quadruplex has a minimal effect on the atomic energies except for the atoms that are closest to the cations, which are largely stabilized in the presence of these ions.
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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 | 0.001 |
| 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) | 0.003 | 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".