A shared binding interface controls Vps13 organelle-specific targeting independently of its vacuolar protein sorting function
Bibliographic record
Abstract
Abstract Yeast vacuolar protein sorting 13 (Vps13) is a bridge-like transporter that directs lipid flow between membranes at organelle contact sites. Vps13 targeting relies on organelle-specific adaptors containing proline-X-proline (PxP) motifs, which compete for binding to the Vps13 adaptor-binding (VAB) domain. Though a VAB-PxP interface has been identified for the mitochondrial adaptor Mcp1, whether other adaptors use identical binding mechanisms is unknown. Moreover, not every Vps13 function is connected to a known PxP adaptor, suggesting other adaptors may exist. Here, we validate the significance of the shared VAB-PxP interface by showing that mutations within this region inhibit both adaptor binding and Vps13 membrane targeting in vivo. Using predictive modeling, we demonstrate that while adaptors share a common Vps13-binding interface, slight differences between these interfaces may contribute to preferential binding and adaptor competition. Notably, we find that the VPS pathway functions independently of the PxP motif binding site, and extensive scanning mutagenesis did not reveal a dedicated VPS-specific adaptor interface. Our results indicate the VPS pathway likely employs a non-PxP adaptor mechanism, yet the structural integrity of the VAB domain remains essential for proper pathway function. Significance statement Adaptor-mediated recruitment of yeast Vps13 to organelles requires a consensus PxP motif. It is unclear if all adaptors bind Vps13 in a similar manner and if all Vps13 functions are dependent on adaptors that contain this motif. We show that Vps13 binds the core PxP motifs from known adaptors through a shared interface, yet this interface is dispensable for Vps13’s role in the vacuole protein sorting pathway. Our work suggests that Vps13 engages in a wider range of targeting mechanisms than was previously recognized, and that the Vps13 adaptor-binding domain must have a function beyond targeting this consensus motif.
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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 | 0.001 |
| 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".