MOLECULAR DYNAMICS SIMULATION STUDIES OF ION TRANSPORT ALONG G-QUADRUPLEX DNA CHANNELS
Bibliographic record
Abstract
Guanine-rich DNA and RNA sequences can fold, in the presence of alkali metal ions such as Na+ and K+, into G-quadruplex structures. These alkali metal ions are necessary for the stabilization of G-quadruplex structures. However, little is known about the ion dynamics in G-quadruplex structures. In this thesis, we used molecular dynamics (MD) simulations to study the energetics of ion transport in G-quadruplex DNA channels. In particular, we applied, for the first time, adaptive biasing force (ABF) and umbrella sampling (US) methods to obtain potential of mean force (PMF) profiles for Na+, K+, and NH4+ ion movement along [d(TG4T)]4 and [d(G3T4G4)]2 channels. We found that the ABF and US methods produce very similar PMF profiles, in qualitative agreement with the very limited experimental data in the literature. We found that, within a G-quadruplex channel, K+ and NH4+ ions experience significant energy barriers (13-17 kcal/mol) to cross a G-quartet, whereas the Na+ movement encounters minimal resistance (5-7 kcal/mol). All ions are nearly fully dehydrated inside the channel but quickly become hydrated after exiting the channel. Our simulations suggested that the free energy landscapes for ion movement between the channel exit points and bulk solution are quite flat (ca. 2-4 kcal/mol) regardless of the loop topology in the region. We discovered that the directional symmetry of the ion movement within any G-quadruplex channel depends critically on both the DNA sequence and the folding of the G-quadrupelx structure. While the ion movement inside the [d(TG4T)]4 channel shows the same free energy barrier in either direction, the [d(G3T4G4)]2 channel exhibits a free energy difference of 3-4 kcal/mol for NH4+ ions exiting from the two ends. We hypothesized that the mode of base-stacking is the determining factor for the G-quartet stiffness and this stiffness then contributes to the free energy barrier for any ion to across it. This hypothesis appears to be consistent with all currently available experimental observations. When a G-quadruplex channel contains multiple ions, we found that the ion-ion repulsion is an important factor that must be considered in order to have a complete understanding of the ion movement within G-quadruplex DNA channels.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".