Development of PROTAC Degrader Drugs for Cancer
Bibliographic record
Abstract
The development of novel drug modalities is necessary to overcome the current critical issues in the treatment of cancer, namely toxicity, insufficient efficacy, and the development of resistance. Unlike classical small molecule inhibitors that only block a single function or interaction of a protein involved in oncogenic signaling, proteolysis-targeting chimeras (PROTACs) degrade the entire protein, thus offering a potential paradigm shift. PROTACs are bivalent small molecules that recruit a target protein in proximity to an E3 ligase, promoting the transfer of ubiquitin, which marks the protein for proteasomal degradation. Because of their unique properties, PROTACs offer an attractive alternative as targeted therapeutics. The first PROTAC entered the clinic 5 years ago, and since then more than 30 have followed. In this review, we discuss the current compounds being investigated in the clinic, the key aspects of their design, and their potential for treating cancer.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".