Insight into the key interactions of bromodomain inhibitors based on molecular docking, interaction fingerprinting, molecular dynamics and binding free energy calculation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The bromodomain is a key protein-protein interaction module that specifically reads the acetylation marks of histones in epigenetic regulation. Currently, lots of inhibitors targeting the bromodomain have been reported as therapeutic agents. To better understand the interaction mechanism of bromodomain inhibitors, 20 diverse bromodomain inhibitors were studied using a combination of computational methods, including molecular docking, interaction fingerprinting, molecular dynamics simulation and binding free energy calculation. As a result, interactions important for the activity were critically analyzed, and the energy contribution in terms of individual residues was explored. These integrated results provided insights into two hot spots in the active site of the bromodomain, where the hydrophobic hot spot formed by Trp81, Val87, Leu92 and Ile146 played a central role in the interaction, and the hydrogen-bond hot spot mediated by Asn140 exhibited a moderate contribution to the binding affinity of the bromodomain inhibitors. This interaction mechanism study may facilitate the rational design of novel small-molecule bromodomain inhibitors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it