Molecular basis for regulation of the class I phosphoinositide 3-kinases (PI3Ks), and their targeting in human disease
Bibliographic record
Abstract
that activates multiple pro-growth signalling pathways. Class I PI3Ks can be activated by multiple plasma membrane stimuli, including G-protein coupled receptors, Ras superfamily GTPases, and receptor tyrosine kinases. The dysregulation of class I PI3Ks is critical in the progression of many human diseases, including cancers, immunodeficiencies, and developmental disorders. Highlighting this is frequent oncogenic mutations (2nd most frequently mutated gene in all human cancers) in PIK3CA encoding the p110α catalytic subunit of class IA PI3K. The class I PI3Ks are obligate heterodimers composed of a catalytic and regulatory subunit, split into two subclasses, class IA and class IB. Recent elucidation of the structures of class I PI3Ks bound to activating stimuli, with activating disease-linked mutations and bound to allosteric conformational selective inhibitors/activators, has revealed extensive insight into the molecular basis of class I PI3K regulation. This review will summarize our current molecular knowledge of class I PI3K regulation, as well as how this information is being used to generate both small molecules and biologics that can either inhibit or activate kinase activity as potential therapeutic agents and biochemical tools.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".