Selenium derivatization of nucleic acids for crystallography
Bibliographic record
Abstract
The high-resolution structure of the DNA (5'-GTGTACA-C-3') with the selenium derivatization at the 2'-position of T2 was determined via MAD and SAD phasing. The selenium-derivatized structure (1.28 A resolution) with the 2'-Se modification in the minor groove is isomorphorous to the native structure (2.0 A). To directly compare with the conventional bromine derivatization, we incorporated bromine into the 5-postion of T4, determined the bromine-derivatized DNA structure at 1.5 A resolution, and found that the local backbone torsion angles and solvent hydration patterns were altered in the structure with the Br incorporation in the major groove. Furthermore, while the native and Br-derivatized DNAs needed over a week to form reasonable-size crystals, we observed that the Se-derivatized DNAs grew crystals overnight with high-diffraction quality, suggesting that the Se derivatization facilitated the crystal formation. In addition, the Se-derivatized DNA sequences crystallized under a broader range of buffer conditions, and generally had a faster crystal growth rate. Our experimental results indicate that the selenium derivatization of DNAs may facilitate the determination of nucleic acid X-ray crystal structures in phasing and high-quality crystal growth. In addition, our results suggest that the Se derivatization can be an alternative to the conventional Br derivatization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".