Molecular Events Initiating Exit of a Copper-transporting ATPase ATP7B from the Trans-Golgi Network
Bibliographic record
Abstract
The copper-transporting ATPase ATP7B has a dual intracellular localization: the trans-Golgi network (TGN) and cytosolic vesicles. Changes in copper levels, kinase-mediated phosphorylation, and mutations associated with Wilson disease alter the steady-state distribution of ATP7B between these compartments. To identify a primary molecular event that triggers ATP7B exit from the TGN, we characterized the folding, activity, and trafficking of the ATP7B variants with mutations within the regulatory N-terminal domain (N-ATP7B). We found that structural changes disrupting the inter-domain contacts facilitate ATP7B exit from the TGN. Mutating Ser-340/341 in the N-ATP7B individually or together to Ala, Gly, Thr, or Asp produced active protein and shifted the steady-state localization of ATP7B to vesicles, independently of copper levels. The Ser340/341G mutant had a lower kinase-mediated phosphorylation under basal conditions and no copper-dependent phosphorylation. Thus, negative charges introduced by copper-dependent phosphorylation are not obligatory for ATP7B trafficking from the TGN. The Ser340/341A mutation did not alter the overall fold of N-ATP7B, but significantly decreased interactions with the nucleotide-binding domain, mimicking consequences of copper binding to N-ATP7B. We propose that structural changes that specifically alter the inter-domain contacts initiate exit of ATP7B from the TGN, whereas increased phosphorylation may be needed to maintain an open interface between the domains.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".