Validation of helical tilt angles in the solution NMR structure of the Z domain of Staphylococcal protein A by combined analysis of residual dipolar coupling and NOE data
Bibliographic record
Abstract
Staphylococcal protein A (SpA) is a virulence factor from Staphylococcus aureus that is able to bind to immunoglobulins. The 3D structures of its immunoglobulin (Ig) binding domains have been extensively studied by NMR and X-ray crystallography, and are often used as model structures in developing de novo or ab initio strategies for predicting protein structure. These small three-helix-bundle structures, reported in free proteins or Ig-bound complexes, have been determined previously using medium- to high-resolution data. Although the location and relative orientation of the three helices in most of these published 3D domain structures are consistent, there are significant differences among the reported structures regarding the tilt angle of the first helix (helix 1). We have applied residual dipolar coupling data, together with nuclear Overhauser enhancement and scalar coupling data, in refining the NMR solution structure of an engineered IgG-binding domain (Z domain) of SpA. Our results demonstrate that the three helices are almost perfectly antiparallel in orientation, with the first helix tilting slightly away from the other two helices. We propose that this high-accuracy structure of the Z domain of SpA is a more suitable target for theoretical predictions of the free domain structure than previously published lower-accuracy structures of protein A domains.
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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".