Targeting bromodomain-containing proteins: research advances of drug discovery
Bibliographic record
Abstract
Bromodomain (BD) is an evolutionarily conserved protein module found in 46 different BD-containing proteins (BCPs). BD acts as a specific reader for acetylated lysine residues (KAc) and serves an essential role in transcriptional regulation, chromatin remodeling, DNA damage repair, and cell proliferation. On the other hand, BCPs have been shown to be involved in the pathogenesis of a variety of diseases, including cancers, inflammation, cardiovascular diseases, and viral infections. Over the past decade, researchers have brought new therapeutic strategies to relevant diseases by inhibiting the activity or downregulating the expression of BCPs to interfere with the transcription of pathogenic genes. An increasing number of potent inhibitors and degraders of BCPs have been developed, some of which are already in clinical trials. In this paper, we provide a comprehensive review of recent advances in the study of drugs that inhibit or down-regulate BCPs, focusing on the development history, molecular structure, biological activity, interaction with BCPs and therapeutic potentials of these drugs. In addition, we discuss current challenges, issues to be addressed and future research directions for the development of BCPs inhibitors. Lessons learned from the successful or unsuccessful development experiences of these inhibitors or degraders will facilitate the further development of efficient, selective and less toxic inhibitors of BCPs and eventually achieve drug application in the clinic.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".