Phasing with calcium at home
Bibliographic record
Abstract
With better tools for data processing and with synchrotron beamlines that are capable of collecting data at longer wavelengths, sulfur-based native single-wavelength anomalous dispersion (SAD) phasing has become the `first-choice' method for de novo protein structure determination. However, for many proteins native SAD phasing can be simplified by taking advantage of their interactions with natural metal cofactors that are stronger anomalous scatterers than sulfur. This is demonstrated here for four unique domains of a 1.5 MDa calcium-dependent adhesion protein using the anomalous diffraction of the chelated calcium ions. In all cases, low anomalous multiplicity X-ray data were collected on a home-source diffractometer equipped with a chromium rotating anode (λ = 2.2909 Å). In all but one case, calcium SAD phasing alone was sufficient to allow automated model building and refinement of the protein model after the calcium substructure had been determined. Given that Ca atoms will be present in a significant percentage of proteins that remain uncharacterized, many aspects of the data-collection and processing methods described here could be broadly applied for routine de novo structure elucidation.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.023 | 0.007 |
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".