Relationship between nucleic acid sequence, structure and function in terms of stabilizing interactions
Bibliographic record
Abstract
The relationship between nucleic acid (NA) sequence, structure and function is intricately connected to the stabilizing interactions (primarily hydrogen bonding and 1t-stacking) that occur between the monomeric subunits that constitute NAs. Therefore, detailed insights into the. nature of the stabilizing interactions would permit the full exploitation of the structure-function relationship in NAs. A complete understanding of the role of the stabilizing interactions in NAs involves the fulfillment of two requirements: 1) The ability to determine the electronic structure of the monomeric units (in terms of the electron density distribution as an observable) that make up the fundamental structure of NAs, which is possible through the use of quantum chemical calculations, and 2) The ability to characterize the electronic structure of these monomeric units in the context of realistic NA structures. Ideally, such molecular structures are determined experimentally. These two ideas are combined into a methodology that has been designed, tested and validated in the work presented here. The proof of concept culminates in the ability of the methodology to exploit the structure-function relationship in NAs through procurement of full stabilization profiles of host NA and guest (small molecule inhibitors to the function of the NA) complexes, where the potential inhibitors were designed on the basis of the stabilization profiles of the host and natural ligand complexes
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".