Post‐synaptic density perturbs insulin‐induced Kv1.3 channel modulation via a clustering mechanism involving the SH<sub>3</sub> domain
Bibliographic record
Abstract
The olfactory bulb (OB) contains the highest concentration of the insulin receptor (IR) kinase in the central nervous system; however, its functional role and modulation in this region remains poorly understood. IR kinase contains a number of proline-rich motifs, making it an excellent candidate for modulation by SH(3) domain-containing adaptor proteins. Kv1.3, a voltage-gated Shaker potassium channel and tyrosine phosphorylation substrate of IR kinase, contains several proline-rich sequences and a canonical post-synaptic density 95 (PSD-95)/discs large/zO-1 domain (PDZ) recognition motif common to most Shaker family members. We sought to determine if a functional relationship existed between Kv1.3, IR kinase, and the SH(3)/PDZ adaptor protein PSD-95. Through patch-clamp electrophysiology, immunochemistry, and co-immunoprecipitation, we found that while Kv1.3 and PSD-95 alone interact via the canonical C-terminal PDZ recognition motif of the channel, this molecular site of interaction acts to cluster the channels but the PSD-95 SH(3)-guanylate kinase domain functionally modulates Kv1.3 activity via two proline-rich domains in its N- and C-terminal. Therefore, these data suggest that adaptor domains responsible for ion-channel clustering and functional modulation are not necessarily coupled. Moreover, IR kinase and Kv1.3 can only be co-immunoprecipitated in the presence of PSD-95 as the adapting linker. Functionally, insulin-dependent Kv1.3 phosphorylation that causes channel current suppression is blocked via interaction with the PSD-95 SH(3)-guanylate kinase domain. Because all the three proteins co-localize in multiple lamina of the OB that are known to be rich in synaptic connections, membrane excitability and synaptic transmission at critical locations in the OB have the capacity to be finely regulated.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".