Base Stacking Configuration is a Major Determinant of Excited State Dynamics in A.T DNA and LNA
Bibliographic record
Abstract
Base stacking plays an important role in excited state dynamics in polynucleotides. However, it is poorly understood how stacking geometries influence the formation of and relaxation from excites states. Natural poly(dA)poly(dT) adopts a B-form structure with extensive geometrical overlap between adjacent stacked adenines while the synthetic, locked ribose analogue (LNA), adopts the A-form structure where such overlap between adjacent adenines is reduced. We have used pump-probe transient absorption measurements on DNA and LNA, with excitation at 260 nm and absorption monitored at 440 and 260 nm, to examine the differences in excited state dynamics in B-and A-form conformations. We observed slow decay times, both early and late stage, from the excited states of B-form and fast decay times from the excited states of analogous homopolymeric A-form structures. Within similar conformations, relaxation times are dependent on the number of stacked adenines as determined by either chain length or sequence. An increase in excited state lifetimes with increase in the number of stacked adenines shows that these excited states can be delocalized over several bases. Thus excited state lifetimes are highly dependent on how the bases are stacked. We conclude from our results that, for identical sequences, conformations that exhibit a high degree of adenine base overlap favor initial cooperative excitation as well as subsequent evolution to delocalized excited states, but hinder the formation of out-of-plane geometries required for fast relaxation to the electronic ground state thus prolonging excited state lifetimes.
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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 | 0.001 |
| 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) | 0.001 | 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".