Sulfur-SAD phasing becomes a routine approach to solve<i>de novo</i>structures
Bibliographic record
Abstract
The recent application of softer X-ray radiation provides an alternative path to solve protein crystal structures in high throughput pace.In-house chromium Kα radiation (λ = 2.29 Å) is one of the most commonly used softer X-ray radiation wavelengths in macromolecular crystallography.Chromium radiation increases the anomalous signal of many intrinsic elements or often used heavy atoms in derivatization.For example, compared to Cu radiation, the contribution to the anomalous term of sulfur and selenium atom doubles to 1.14 e and 2.28 e, respectively.These enhanced anomalous signals are sufficient to be routinely collected and processed with modern instrumentation and software packages.This work reports several examples of protein structures solved using sulfur-SAD phasing.For these proteins it was difficult to produce or crystallize the selenium-methionine substituted form, or to reproduce more of the original crystals.In other words, the native forms of these crystals had to be used to solve their structures.A single data set was collected with an in-house Cr X-ray radiation source for each protein crystal and was phased by the S-SAD phasing approach.These examples demonstrate that Cr radiation has become a routine phasing approach in the crystallographer's toolkit, which makes it possible to solve a crystal structure with native crystals only or before synchrotron data collection when selenium-methionine substituted protein is not available.This method clearly improves the productivity of macromolecular structure determination, usage of synchrotron beam time and helps enhance high throughput structure determination.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.036 | 0.009 |
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".