The double lives of phosphatases of regenerating liver: A structural view of their catalytic and noncatalytic activities
Bibliographic record
Abstract
Phosphatases of regenerating liver (PRLs) are protein phosphatases involved in the control of cell growth and migration. They are known to promote cancer metastasis but, despite over 20 years of study, there is still no consensus about their mechanism of action. Recent work has revealed that PRLs lead double lives, acting both as catalytically active enzymes and as pseudophosphatases. The three known PRLs belong to the large family of cysteine phosphatases that form a phosphocysteine intermediate during catalysis. Uniquely to PRLs, this intermediate is stable, with a lifetime measured in hours. As a consequence, PRLs have very little phosphatase activity. Independently, PRLs also act as pseudophosphatases by binding CNNM membrane proteins to regulate magnesium homeostasis. In this function, an aspartic acid from CNNM inserts into the phosphatase catalytic site of PRLs, mimicking a substrate-enzyme interaction. The delineation of PRL pseudophosphatase and phosphatase activities in vivo was impossible until the recent identification of PRL mutants defective in one activity or the other. These mutants showed that CNNM binding was sufficient for PRL oncogenicity in one model of metastasis, but left unresolved its role in other contexts. As the presence of phosphocysteine prevents CNNM binding and CNNM-binding blocks catalytic activity, these two activities are inherently linked. Additional studies are needed to untangle the intertwined catalytic and noncatalytic functions of PRLs. Here, we review the current understanding of the structure and biophysical properties of PRL phosphatases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".