Dimerization interface of osteoprotegerin revealed by hydrogen–deuterium exchange mass spectrometry
Bibliographic record
Abstract
Previous structural studies of osteoprotegerin (OPG), a crucial negative regulator of bone remodeling and osteoclastogenesis, were mostly limited to the N-terminal ligand-binding domains. It is now known that the three C-terminal domains of OPG also play essential roles in its function by mediating OPG dimerization, OPG-heparan sulfate (HS) interactions, and formation of the OPG-HS-receptor activator of nuclear factor κB ligand (RANKL) ternary complex. Employing hydrogen-deuterium exchange MS methods, here we investigated the structure of full-length OPG in complex with HS or RANKL in solution. Our data revealed two noteworthy aspects of the OPG structure. First, we found that the interconnection between the N- and C-terminal domains is much more rigid than previously thought, possibly because of hydrophobic interactions between the fourth cysteine-rich domain and the first death domain. Second, we observed that two hydrophobic clusters located in two separate C-terminal domains directly contribute to OPG dimerization, likely by forming a hydrophobic dimerization interface. Aided by site-directed mutagenesis, we further demonstrated that an intact dimerization interface is essential for the biological activity of OPG. Our study represents an important step toward deciphering the structure-function relationship of the full-length OPG protein.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".