Order and disorder – an integrative structure of the full-length human growth hormone receptor
Bibliographic record
Abstract
ABSTRACT Despite the many physiological and pathophysiological functions of the human growth hormone receptor (hGHR), a detailed understanding of its modus operandi is hindered by the lack of structural information of the entire receptor at the molecular level. Due to its relatively small size (70 kDa) and large content of structural disorder (>50%), this membrane protein falls between the cracks of conventional high-resolution structural biology methods. Here, we study the structure of the full-length hGHR in nanodiscs with small angle-X-ray scattering (SAXS) as the foundation. We developed an approach in which we combined SAXS, X-ray diffraction and NMR spectroscopy obtained on the individual domains and integrated the data through molecular dynamics simulations to interpret SAXS data on the full-length hGHR in nanodiscs. The structure of the hGHR was determined in its monomeric state and provides the first experimental model of any full-length cytokine receptor in a lipid membrane. Combined, our results highlight that the three domains of the hGHR are free to reorient relative to each other, resulting in a broad structural ensemble. Our work exemplifies how integrating experimental data from several techniques computationally, may enable the characterization of otherwise inaccessible structures of membrane proteins with long disordered regions, a widespread phenomenon in biology. To understand orchestration of cellular signaling by disordered chains, the hGHR is archetypal and its structure emphasizes that we need to take a much broader, ensemble view on signaling.
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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".