Caught in the act – protein adaptation and the expanding roles of the PACS proteins in tissue homeostasis and disease
Bibliographic record
Abstract
Vertebrate proteins that fulfill multiple and seemingly disparate functions are increasingly recognized as vital solutions to maintaining homeostasis in the face of the complex cell and tissue physiology of higher metazoans. However, the molecular adaptations that underpin this increased functionality remain elusive. In this Commentary, we review the PACS proteins - which first appeared in lower metazoans as protein traffic modulators and evolved in vertebrates to integrate cytoplasmic protein traffic and interorganellar communication with nuclear gene expression - as examples of protein adaptation 'caught in the act'. Vertebrate PACS-1 and PACS-2 increased their functional density and roles as metabolic switches by acquiring phosphorylation sites and nuclear trafficking signals within disordered regions of the proteins. These findings illustrate one mechanism by which vertebrates accommodate their complex cell physiology with a limited set of proteins. We will also highlight how pathogenic viruses exploit the PACS sorting pathways as well as recent studies on PACS genes with mutations or altered expression that result in diverse diseases. These discoveries suggest that investigation of the evolving PACS protein family provides a rich opportunity for insight into vertebrate cell and organ homeostasis.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".