Phosphorylation-induced conformational dynamics in an intrinsically disordered protein and potential role in phenotypic heterogeneity
Bibliographic record
Abstract
Intrinsically disordered proteins (IDPs) that lack a unique 3D structure and comprise a large fraction of the human proteome play important roles in numerous cellular functions. Prostate-Associated Gene 4 (PAGE4) is an IDP that acts as a potentiator of the Activator Protein-1 (AP-1) transcription factor. Homeodomain-Interacting Protein Kinase 1 (HIPK1) phosphorylates PAGE4 at S9 and T51, but only T51 is critical for its activity. Here, we identify a second kinase, CDC-Like Kinase 2 (CLK2), which acts on PAGE4 and hyperphosphorylates it at multiple S/T residues, including S9 and T51. We demonstrate that HIPK1 is expressed in both androgen-dependent and androgen-independent prostate cancer (PCa) cells, whereas CLK2 and PAGE4 are expressed only in androgen-dependent cells. Cell-based studies indicate that PAGE4 interaction with the two kinases leads to opposing functions. HIPK1-phosphorylated PAGE4 (HIPK1-PAGE4) potentiates c-Jun, whereas CLK2-phosphorylated PAGE4 (CLK2-PAGE4) attenuates c-Jun activity. Consistent with the cellular data, biophysical measurements (small-angle X-ray scattering, single-molecule fluorescence resonance energy transfer, and NMR) indicate that HIPK1-PAGE4 exhibits a relatively compact conformational ensemble that binds AP-1, whereas CLK2-PAGE4 is more expanded and resembles a random coil with diminished affinity for AP-1. Taken together, the results suggest that the phosphorylation-induced conformational dynamics of PAGE4 may play a role in modulating changes between PCa cell phenotypes. A mathematical model based on our experimental data demonstrates how differential phosphorylation of PAGE4 can lead to transitions between androgen-dependent and androgen-independent phenotypes by altering the AP-1/androgen receptor regulatory circuit in PCa cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".