<i>In silico</i>investigation of PARP-1 catalytic domains in<i>holo</i>and<i>apo</i>states for the design of high-affinity PARP-1 inhibitors
Bibliographic record
Abstract
The rational design of high-affinity inhibitors of poly-ADP-ribose polymerase-1 (PARP-1) is at the heart of modern anti-cancer drug design. While relevance of enzyme to DNA repair processes in cellular environment is firmly established, the structural and functional understanding of the main determinants for high-affinity ligands controlling PARP-1 activity is still lacking. The conserved active site of PARP-1 represents an ideal target for inhibitors and may offer a novel target at the treatment of breast cancer. To fill the gap in the structural knowledge, we report on the combination of molecular dynamics (MD) simulations, principal component analysis (PCA), and conformational analysis that analyzes in great details novel binding mode for a number of inhibitors at the PARP-1. While optimization of the binding affinity for original target is an important goal in the drug design, many of the promising molecules for treatment of the breast cancer are plagued by significant cardiotoxicity. One of the most common side-effects reported for a number of polymerase inhibitors is its off-target interactions with cardiac ion channels and hERG1 channel, in particular. Thus, selected candidate PARP-1 inhibitors were also screened in silico at the central cavities of hERG1 potassium ion channel.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".