An analgesic peptide H-20 attenuates chronic pain via the PD-1 pathway with few adverse effects.
Long ZhaoHao LuoYu MaShengze ZhuYongJiang WuMuxing LuXiao-Jun YaoXin LiuGang ChenPublished in: Proceedings of the National Academy of Sciences of the United States of America (2022)
The lack of effective and safe analgesics for chronic pain management has been a health problem associated with people's livelihoods for many years. Analgesic peptides have recently shown significant therapeutic potential, as they are devoid of opioid-related adverse effects. Programmed cell death protein 1 (PD-1) is widely expressed in neurons. Activation of PD-1 by PD-L1 modulates neuronal excitability and evokes significant analgesic effects, making it a promising target for pain treatment. However, the research and development of small molecule analgesic peptides targeting PD-1 have not been reported. Here, we screened the peptide H-20 using high-throughput screening. The in vitro data demonstrated that H-20 binds to PD-1 with micromolar affinity, evokes Src homology 2 domain-containing tyrosine phosphatase 1 (SHP-1) phosphorylation, and diminishes nociceptive signals in dorsal root ganglion (DRG) neurons. Preemptive treatment with H-20 effectively attenuates perceived pain in naïve WT mice. Spinal H-20 administration displayed effective and longer-lasting analgesia in multiple preclinical pain models with a reduction in or absence of tolerance, abuse liability, constipation, itch, and motor coordination impairment. In summary, our findings reveal that H-20 is a promising candidate drug that ameliorates chronic pain in the clinic.
Keyphrases
- chronic pain
- pain management
- neuropathic pain
- spinal cord
- small molecule
- spinal cord injury
- healthcare
- mental health
- anti inflammatory
- protein protein
- amino acid
- public health
- depressive symptoms
- health information
- mass spectrometry
- mesenchymal stem cells
- stem cells
- primary care
- gene expression
- metabolic syndrome
- skeletal muscle
- protein kinase
- single cell
- machine learning
- electronic health record
- social media
- subarachnoid hemorrhage
- data analysis
- tyrosine kinase
- social support
- cerebral ischemia