Identification and Mechanistic Characterization of a Peptide Inhibitor of Glycogen Synthase Kinase (GSK3β) Derived from the Disrupted in Schizophrenia 1 (DISC1) Protein
Bibliographic record
Abstract
ABSTRACT Glycogen Synthase Kinase 3-beta (GSK3β) is a critical regulator of several cellular pathways involved in neuroplasticity and is a potential target for neurotherapeutic development in the treatment of neuropsychiatric and neurodegenerative diseases. The majority of efforts to develop inhibitors of GSK3β have been focused on developing small molecule inhibitors that compete with ATP through direct interaction with the ATP binding site. This strategy has presented selectivity challenges due to the evolutionary conservation of this domain within the kinome. The Disrupted in Schizophrenia (DISC1) protein, has previously been shown to bind and inhibit GSK3β activity. Here, we report the characterization of a 44-mer peptide derived from human DISC1 (hDISCtide) that is sufficient to both bind and inhibit GSK3β in a non-competitive mode that is distinct from classical ATP competitive inhibitors. Based on multiple independent biochemical and biophysical assays, we propose that hDISCtide interacts at two distinct regions of GSK3β: an inhibitory region that partially overlaps with the binding site of FRATide, a well-known GSK3β binding peptide, and a specific binding region that is unique to hDISCtide. Taken together, our findings present a novel avenue for developing a peptide-based selective inhibitor of GSK3β.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".