The motif EXEXXXL in the cytosolic tail of the secretory human proprotein convertase PC7 regulates its trafficking and cleavage activity
Bibliographic record
Abstract
Many secretory proteins are activated by cleavage at specific sites. The proprotein convertases (PCs) form a family of nine secretory subtilisin-like serine proteases, seven of which cleave at specific basic residues within the trans -Golgi network, granules, or at the cell surface/endosomes. The seventh member, PC7, is a type-I transmembrane (TM) protein with a 97-residue–long cytosolic tail (CT). PC7 sheds human transferrin receptor 1 (hTfR1) into soluble shTfR1 in endosomes. To better understand the physiological roles of PC7, here we focused on the relationship between the CT-regulated trafficking of PC7 and its ability to shed hTfR1. Deletion of the TMCT resulted in soluble PC7 and loss of its hTfR1 shedding activity. Extensive CT deletions and mutagenesis analyses helped us zoom in on three residues in the CT, namely Glu-719, Glu-721, and Leu-725, that are part of a novel motif, E X E XXX L 725 , critical for PC7 activity on hTfR1. NMR studies of two 14-mer peptides mimicking this region of the CT and its Ala variants revealed that the three exposed residues are on the same side of the molecule. This led to the identification of adaptor protein 2 (AP-2) as a protein that recognizes the E X E XXX L 725 motif, thus representing a potentially new regulator of PC7 trafficking and cleavage activity. Immunocytochemistry of the subcellular localization of PC7 and its Ala variants of Leu-725 and Glu-719 and Glu-721 revealed that Leu-725 enhances PC7 localization to early endosomes and that, together with Glu-719 and Glu-721, it increases the endosomal activity of PC7 on hTfR1.
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) | 0.001 | 0.001 |
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".