Small Organic Molecule Disruptors of Cav3.2 - USP5 Interactions Reverse Inflammatory and Neuropathic Pain
Bibliographic record
Abstract
BACKGROUND: Cav3.2 channels facilitate nociceptive transmission and are upregulated in DRG neurons in response to nerve injury or peripheral inflammation. We reported that this enhancement of Cav3.2 currents in afferent neurons is mediated by deubiquitination of the channels by the deubiquitinase USP5, and that disrupting USP5/Cav3.2 channel interactions protected from inflammatory and neuropathic pain. RESULTS: Here we describe the development of a small molecule screening assay for USP5-Cav3.2 disruptors, and report on two hits of a ~5000 compound screen - suramin and the flavonoid gossypetin. In mouse models of inflammatory pain and neuropathic pain, both suramin and gossypetin produced dose-dependent and long-lasting mechanical anti-hyperalgesia that was abolished or greatly attenuated in Cav3.2 null mice. Suramin and Cav3.2/USP5 Tat-disruptor peptides were also tested in models of diabetic neuropathy and visceral pain, and provided remarkable protection. CONCLUSIONS: Overall, our findings provide proof of concept for a new class of analgesics that target T-type channel deubiquitination.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".