Molecular Basis of Interchain Disulfide Bond Formation in BMP-9 and BMP-10
Bibliographic record
Abstract
BMP-9 and BMP-10 are TGF-β family signaling ligands naturally secreted into blood. They act on endothelial cells and are required for proper development and maintenance of the vasculature. In hereditary hemorrhagic telangiectasia, regulation is disrupted due to mutations in the BMP-9/10 pathway, namely in the type I receptor ALK1 or the co-receptor endoglin. It has been demonstrated that BMP-9/10 heterodimers are the most abundant signaling species in the blood, but it is unclear how they form. Unlike other ligands of the TGF-β family, BMP-9 and -10 are secreted as a mixture of disulfide-linked dimers and monomers, in which the interchain cysteine (Cys-392) remains either paired or unpaired. Here, we show that the monomers are secreted in a cysteinylated form that crystallizes as a non-covalent dimer. Despite this, monomers do not self-associate at micromolar or lower concentrations and have reduced signaling potency compared to disulfide-linked dimers. We further show using protein crystallography that the interchain disulfide of the BMP-9 homodimer adopts a highly strained syn-periplanar conformation. Hence, geometric strain across the interchain disulfide is responsible for infrequent interchain disulfide bond formation, not the cysteinylation. Additionally, we show that interchain disulfide bond formation occurs less in BMP-9 than BMP-10 and these frequencies can be reversed by swapping residues near the interchain disulfide that form attractive interactions with the opposing protomer. Finally, we discuss the implications of these observations on BMP-9/10 heterodimer formation.
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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".