Protein kinase C isozymes and their selectivity towards ruboxistaurin
Bibliographic record
Abstract
Protein kinase C (PKC) isozymes are an important class of enzymes in cell signaling and as drug targets. They are involved in specific pathways and have selectivity towards certain ligands, despite their high sequence similarities. Ruboxistaurin is a specific inhibitor of PKC-beta. To understand the molecular determinants for the selectivity of ruboxistaurin, we derived the three-dimensional structures of the kinase domains of PKC-alpha, -betaI, and -zeta using homology modeling. Several binding orientations of ruboxistaurin in the binding sites of these PKC catalytic domains were analyzed, and a putative alternative binding site for PKC-zeta was identified in its kinase domain. The calculated free energy of binding correlates well with the IC(50) of the inhibitor against each PKC isozyme. A residue-based energy decomposition analysis attributed the binding free energy to several key residues in the catalytic sites of these enzymes, revealing potential protein-ligand interactions responsible for ligand binding. The contiguous binding site revealed in the catalytic domain of PKC-zeta provides avenues for selective drug design. The details of structural nuances for specific inhibition of PKC isozymes are presented in the context of the three-dimensional structures of this important class of enzymes.
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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) | 0.000 | 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) | 0.001 | 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 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".