Phospho-Form Specific Substrates of Protein Kinase B (AKT1)
Bibliographic record
Abstract
Protein kinase B (AKT1) is hyper-activated in diverse human tumors. AKT1 is activated by phosphorylation at two key regulatory sites, Thr308 and Ser473. Active AKT1 phosphorylates many, perhaps hundreds, of downstream cellular targets in the cytosol and nucleus. AKT1 is well-known for phosphorylating proteins that regulate cell survival and apoptosis, however, the full catalog of AKT1 substrates remains unknown. Using peptide arrays, we recently discovered that each phosphorylated form of AKT1 (pAKT1S473, pAKT1T308, and ppAKT1S473,T308) has a distinct substrate specificity, and these data were used to predict potential new AKT1 substrates. To test the high-confidence predictions, we synthesized target peptides representing putative AKT1 substrates. Peptides substrates were synthesized by solid phase synthesis and their purity was confirmed by mass spectrometry. Most of the predicted peptides showed phosphate accepting activity similar to or greater than that observed with a peptide derived from a well-established AKT1 substrate, glycogen synthase kinase 3β (GSK-3β). Among the novel substrates, AKT1 was most active with peptides representing PIP3-binding protein Rab11 family-interacting protein 2 and cysteinyl leukotriene receptor 1, indicating their potential role in AKT1-dependent cellular signaling. The ppAKT1S473,T308 enzyme was highly selective for peptides containing a patch of basic residues at −5, −4, −3 and aromatic residues (Phe/Tyr) at +1 positions from the phosphorylation site. The pAKT1S473 variant preferred more acidic peptides, Ser or Pro at +4, and was agnostic to the residue at −5. The data further support our hypothesis that Ser473 phosphorylation plays a key role in modulating AKT1 substrate selectivity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 0.003 |
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".