ATP alters IKK‐2 inhibitor affinity for IKK2 enzyme and reveals non‐equivalent inhibitor binding sites
Bibliographic record
Abstract
Method Inhibitor off‐rate was measured by two methods: (1) pre‐binding the enzyme with inhibitor followed by measuring the recovery of enzyme activity upon a 200‐fold dilution of the enzyme‐inhibitor complex in the presence of 1mM ATP and (2) measuring the shift in the compound potency (IC50) curves obtained by prebinding the enzyme and inhibitor in the absence of ATP followed by addition of either 1μM or 1mM ATP. Results Three literature inhibitors with potency (IC50) ranging from <1 to 35 nM were used for this study: PHA‐408 (Pfizer), GSK‐082 (GSK), and AVE‐002 (Aventis). The off‐rates (T1/2) measured by the dilution method are 124 and <15 min for PHA‐408 and GSK‐082, respectively. The off‐rate for AVE‐002 was biphasic with half of the enzyme‐inhibitor complex dissociating immediately (T1/2 < 2 min) and the other half bound tightly (T1/2 54 min). The IC50 curves at 1μM and 1mM ATP for PHA‐408 showed no shift using a short 2 min assay and is consistent with the slow off‐rate. GSK‐082 showed a > 10 fold loss of potency with 1mM ATP, as expected for a fast off‐rate inhibitor. AVE‐002 IC50 curve with 1μM ATP was monophasic but displayed a biphasic response with 1mM ATP. Conclusion ATP can change the off‐rate of IKK‐2 inhibitor bound to the enzyme. Additionally, high ATP revealed that AVE‐002 bound in the two inhibitor binding sites of the IKK‐2 homodimer non‐equivalently.
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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 | 0.001 | 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 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".