Primary and Secondary Dimer Interfaces of the Fibroblast Growth Factor Receptor 3 Transmembrane Domain: Characterization via Multiscale Molecular Dynamics Simulations
Bibliographic record
Abstract
Receptor tyrosine kinases are single-pass membrane proteins that form dimers within the membrane. The interactions of their transmembrane domains (TMDs) play a key role in dimerization and signaling. Fibroblast growth factor receptor 3 (FGFR3) is of interest as a G380R mutation in its TMD is the underlying cause of ~99% of the cases of achondroplasia, the most common form of human dwarfism. The structural consequences of this mutation remain uncertain: the mutation shifts the position of the TMD relative to the lipid bilayer but does not alter the association free energy. We have combined coarse-grained and all-atom molecular dynamics simulations to study the dimerization of wild-type, heterodimer, and mutant FGFR3 TMDs. The simulations reveal that the helices pack together in the dimer to form a flexible interface. The primary packing mode is mediated by a Gx3G motif. There is also a secondary dimer interface that is more highly populated in heterodimer and mutant configurations that may feature in the molecular mechanism of pathology. Both coarse-grained and atomistic simulations reveal a significant shift of the G380R mutant dimer TMD relative to the bilayer to allow interactions of the arginine side chain with lipid headgroup phosphates.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".