The Structures of COPII Coats and Cages
Bibliographic record
Abstract
Coat protein complex II (COPII) vesicles are responsible for packaging and transporting over 10,000 different cargo molecules (about one‐third of the eukaryotic genome) of widely varying sizes and shapes from the endoplasmic reticulum (ER) to downstream compartments of the secretory pathway. Proteins involved in generating COPII vesicles include the GTPase Sar1, the cargo adaptor Sec23/24, and the cage scaffold Sec13/31. We previously showed that Sec13/31 can self‐assemble into a novel cuboctahedron cage, leading us to suggest that Sec13/31 may form cages of increasing size based on the simple rule that the geometry of the cage is dictated by four Sec13/31 heterotetramers combining to form a vertex. We have now solved the structure of an icosidodecahedral COPII coat assembled from both Sec13/31 and Sec23/24 by cryo‐electron microscopy (cryoEM) and single particle reconstruction. This new structure reveals for the first time the structure of the adaptor layer and reveals possible mechanisms for the coordination of adaptor interaction with cage formation and for the collection of cargo of varying size. We fit a crystal structure of the Sec13/31 heterotetramer into the cuboctahedron and icosidodecahedron structures, and this lead us to propose a molecular mechanism by which the COPII system can accommodate cargo of diverse sizes and shapes.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".