Regulation of Mitogen-Activated Protein Kinase Signaling Pathways by the Ubiquitin-Proteasome System and Its Pharmacological Potential
Bibliographic record
Abstract
Mitogen-activated protein kinase (MAPK) cascades are evolutionarily conserved signaling pathways that play essential roles in transducing extracellular environmental signals into diverse cellular responses to maintain homeostasis. These pathways are classically organized into an architecture of three sequentially acting protein kinases: a MAPK kinase kinase that phosphorylates and activates a MAPK kinase, which in turn phosphorylates and activates the effector MAPK. The activity of MAPKs is tightly regulated by phosphorylation of their activation loop, which can be modulated by positive and negative feedback mechanisms to control the amplitude and duration of the signal. The signaling outcomes of MAPK pathways are further regulated by interactions of MAPKs with scaffolding and regulatory proteins. Accumulating evidence indicates that, in addition to these mechanisms, MAPK signaling is commonly regulated by ubiquitin-proteasome system (UPS)-mediated control of the stability and abundance of MAPK pathway components. Notably, the biologic activity of some MAPKs appears to be regulated mainly at the level of protein turnover. Recent studies have started to explore the potential of targeted protein degradation as a powerful strategy to investigate the biologic functions of individual MAPK pathway components and as a new therapeutic approach to overcome resistance to current small-molecule kinase inhibitors. Here, we comprehensively review the mechanisms, physiologic importance, and pharmacological potential of UPS-mediated protein degradation in the control of MAPK signaling. SIGNIFICANCE STATEMENT: Accumulating evidence highlights the importance of targeted protein degradation by the ubiquitin-proteasome system in regulating and fine-tuning the signaling output of mitogen-activated protein kinase (MAPK) pathways. Manipulating protein levels of MAPK cascade components may provide a novel approach for the development of selective pharmacological tools and therapeutics.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".