Structural Studies of Macromolecules in Solution using Small Angle X-Ray Scattering
Bibliographic record
Abstract
Protein-protein interactions involving proteins with multiple globular domains present technical challenges for determining how such complexes form and how the domains are oriented/positioned. Here, a protocol with the potential for elucidating which specific domains mediate interactions in multicomponent system through ab initio modeling is described. A method for calculating solution structures of macromolecules and their assemblies is provided that involves integrating data from small angle X-ray scattering (SAXS), chromatography, and atomic resolution structures together in a hybrid approach. A specific example is that of the complex of full-length nidogen-1, which assembles extracellular matrix proteins and forms an extended, curved nanostructure. One of its globular domains attaches to laminin γ-1, which structures the basement membrane. This provides a basis for determining accurate structures of flexible multidomain protein complexes and is enabled by synchrotron sources coupled with automation robotics and size exclusion chromatography systems. This combination allows rapid analysis in which multiple oligomeric states are separated just prior to SAXS data collection. The analysis yields information on the radius of gyration, particle dimension, molecular shape and interdomain pairing. The protocol for generating 3D models of complexes by fitting high-resolution structures of the component proteins is also given.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".