Discovery of a peripherally restricted α2AAR agonist as a safe and broad-spectrum oral analgesic
Abstract
The development of safe, non-opioid analgesics remains a pressing challenge. The α2A-adrenergic receptor (α2AAR) is a valid analgesic target, yet clinical translation has been hindered by dose-limiting central side effects. We discover CC10137, an orally bioavailable, peripherally restricted α2AAR agonist that produces a robust, dose-dependent anti-allodynic effect across eight murine pain models, without causing sedation, hypotension, or hypothermia. Co-administration of CC10137 (1 mg/kg, p.o.) and morphine (1 mg/kg s.c.) robustly reverses allodynia by 86% in a neuropathic pain model, surpassing either drug alone (∼45%) or a 3-fold higher morphine dose (3 mg/kg, s.c., 65%). This synergy is further replicated in a cancer pain model. Unlike morphine, CC10137 does not impair spinal nociceptive reflex in a tail-flick model, preserving an essential protective mechanism. CC10137 can thus selectively suppress allodynia under a broad spectrum of pathological pain conditions with a favorable safety profile, highlighting its potential as a standalone or combination therapeutic for chronic pain.
Read the paper
Related studies
- Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min
- De Novo Transcriptome Analysis and Detection of Antimicrobial Peptides of the American Cockroach Periplaneta americana (Linnaeus)
- Molecular Characterization and Expression Profiling of Tomato GRF Transcription Factor Family Genes in Response to Abiotic Stresses and Phytohormones
- Assembly of Tight Junction Strands: Claudin-10b and Claudin-3 Form Homo Tetrameric Building Blocks that Polymerise in a Channel-Independent Manner
- Update of the Pompe variant database for the prediction of clinical phenotypes: Novel disease‐associated variants, common sequence variants, and results from newborn screening
- Machine Learning-Based SERS Chemical Space for Two-Way Prediction of Structures and Spectra of Untrained Molecules
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.