Structural insights into the mechanism of leptin receptor activation
Bibliographic record
Abstract
Leptin is an adipocyte-derived protein hormone that promotes satiety and energy homeostasis by activating the leptin receptor (LepR)-STAT3 signaling axis in a subset of hypothalamic neurons. Leptin signaling is dysregulated in obesity, however, where appetite remains elevated despite high levels of circulating leptin. To gain insight into the mechanism of leptin receptor activation, here we determine the structure of a stabilized leptin-bound LepR signaling complex using single particle cryo-EM. The structure reveals an asymmetric architecture in which a single leptin induces LepR dimerization via two distinct receptor-binding sites. Analysis of the leptin-LepR binding interfaces reveals the molecular basis for human obesity-associated mutations. Structure-based design of leptin variants that destabilize the asymmetric LepR dimer yield both partial and biased agonists that partially suppress STAT3 activation in the presence of wild-type leptin and decouple activation of STAT3 from LepR negative regulators. Together, these results reveal the structural basis for LepR activation and provide insights into the differential plasticity of signaling pathways downstream of LepR.
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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".