Identification of Small-Molecule Inhibitors of Human Inositol Hexakisphosphate Kinases by High-Throughput Screening
Why this work is in the frame
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Bibliographic record
Abstract
Inositol hexakisphosphate kinases (IP6Ks) catalyze pyrophosphorylation of inositol hexakisphosphate (IP6) into inositol 5-diphospho-1,2,3,4,6-pentakisphosphate (IP7), which is involved in numerous areas of cell physiology including glucose homeostasis, blood coagulation, and neurological development. Inhibition of IP6Ks may be effective for the treatment of Type II diabetes, obesity, metabolic complications, thrombosis, and psychiatric disorders. We performed a high-throughput screen (HTS) of 158 410 compounds for IP6K1 inhibitors using a previously developed ADP-Glo Max assay. Of these, 1206 compounds were found to inhibit IP6K1 kinase activity by more than 25%, representing a 0.8% hit rate. Structural clustering analysis of HTS-active compounds, which were confirmed in the dose-response testing using the same kinase assay, revealed diverse clusters that were feasible for future structure-activity relationship (SAR) optimization to potent IP6K inhibitors. Medicinal chemistry SAR efforts in three chemical series identified potent IP6K1 inhibitors which were further validated in an orthogonal LC-MS IP7 analysis. The effects of IP6K1 inhibitors on cellular IP7 levels were further confirmed and were found to correlate with cellular IP6K1 binding measured by a high-throughput cellular thermal shift assay (CETSA).
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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 | 0.001 |
| 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 it