ATP-competitive inhibitors of PI3K enzymes demonstrate an isoform selective dual action by controlling membrane binding
Bibliographic record
Abstract
PI3Kα, consisting of the p110α isoform of the catalytic subunit of PI 3-kinase (encoded by PIK3CA) and the p85α regulatory subunit (encoded by PI3KR1) is activated by growth factor receptors. The identification of common oncogenic mutations in PIK3CA has driven the development of many inhibitors that bind to the ATP-binding site in the p110α subunit. Upon activation, PI3Kα undergoes conformational changes that promote its membrane interaction and catalytic activity, yet the effects of ATP-site directed inhibitors on the PI3Kα membrane interaction are unknown. Using FRET and biolayer interferometry assays, we show that a class of ATP-site directed inhibitors represented by GSK2126458 block the growth factor activated PI3KαWT membrane interaction, an activity dependent on the ligand forming specific ATP-site interactions. The membrane interaction for hot spot oncogenic mutations that bypass normal p85α regulatory mechanisms was insensitive to GSK2126458, while GSK2126458 could regulate mutations found outside of these hot spot regions. Our data show that the effect of GSK126458 on the membrane interaction requires the enzyme to revert from its growth factor activated state to a basal state. We find that an ATP substrate analogue can increase the wild type PI3Kα membrane interaction, uncovering a substrate based regulatory event that can be mimicked by different inhibitor chemotypes. Our findings, together with the discovery of small molecule allosteric activators of PI3Kα illustrate that PI3Kα membrane interactions can be modulated by factors related to ligand binding both within the ATP site and at allosteric sites.
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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 | 0.001 |
| 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".