Agarose gel facilitates enzyme crystal soaking with a ligand analog
Bibliographic record
Abstract
Orthorhombic crystals of the enzyme aspartyl-tRNA synthetase (AspRS) were prepared in agarose gel, a chemical alternative to microgravity or nano-volume drops. Besides providing a convection-free medium, the network of the polysaccharide improved the stability of the crystalline lattice during soaking with L-aspartol adenylate, a synthetic and non-hydrolysable analog of the catalytic intermediate aspartyl adenylate. When crystals were embedded in the polysaccharide matrix the ligand reached their surfaces more uniformly. Gel-grown crystals exhibited well defined reflections even at high resolution and low mosaicity values, despite their fairly high solvent content and the relatively harsh flash cooling procedure. By contrast, soaked AspRS crystals prepared in solution broke apart within 10–30 s after the ligand was introduced into the mother liquor, and subsequently these fragments became an amorphous precipitate. A general objection to the use of gels in protein crystallization is that chemical interactions may occur between the polysaccharide matrix and proteins or ligands. The example of AspRS shows that this is not a major concern. This method may be generally applicable to crystal soaking with other small molecules or heavy atoms.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".