Multiple Phosphoinositide 3-Kinase-Dependent Steps in Activation of Protein Kinase B
Bibliographic record
Abstract
The protein kinase B (PKB)/Akt family of serine kinases is rapidly activated following agonist-induced stimulation of phosphoinositide 3-kinase (PI3K). To probe the molecular events important for the activation process, we employed two distinct models of posttranslational inducible activation and membrane recruitment. PKB induction requires phosphorylation of two critical residues, threonine 308 in the activation loop and serine 473 near the carboxyl terminus. Membrane localization of PKB was found to be a primary determinant of serine 473 phosphorylation. PI3K activity was equally important for promoting phosphorylation of serine 473, but this was separable from membrane localization. PDK1 phosphorylation of threonine 308 was primarily dependent upon prior serine 473 phosphorylation and, to a lesser extent, localization to the plasma membrane. Mutation of serine 473 to alanine or aspartic acid modulated the degree of threonine 308 phosphorylation in both models, while a point mutation in the substrate-binding region of PDK1 (L155E) rendered PDK1 incapable of phosphorylating PKB. Together, these results suggest a mechanism in which 3' phosphoinositide lipid-dependent translocation of PKB to the plasma membrane promotes serine 473 phosphorylation, which is, in turn, necessary for PDK1-mediated phosphorylation of threonine 308 and, consequentially, full PKB activation.
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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 | 0.001 |
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".