Multifaceted targeted protein degradation systems for different cellular compartments
Bibliographic record
Abstract
Selective protein degradation maintains cellular homeostasis, but this process is disrupted in many diseases. Targeted protein degradation (TPD) approaches, built upon existing cellular mechanisms, are promising methods for therapeutically regulating protein levels. Here, we review the diverse palette of tools that are now available for doing so throughout the gene expression pathway and in specific cellular compartments. These include methods for directly removing targeted proteins via the ubiquitin proteasome system with proteolysis targeting chimeras (PROTACs) or dephosphorylation targeting chimeras (DEPTACs). Similar effects can also be achieved through the lysosomal system with autophagy-targeting chimeras (AUTACs), autophagosome tethering compounds (ATTECs), and lysosome targeting chimeras (LYTACs). Other methods act upstream to degrade RNAs (ribonuclease targeting chimeras; RIBOTACs) or transcription factors (transcription factor targeting chimeras; TRAFTACs), offering control throughout the gene expression process. We highlight the evolution and function of these methods and discuss their clinical implications in diverse disease contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".