ABSTRACT
Pharmacological investigations have substantiated the potential of bifunctional opioid/cannabinoid agonists in delivering potent analgesia while minimizing adverse reactions. Peptide modulators of cannabinoid receptors, known as pepcans, have been investigated before. In this study, we designed a series of chimeric peptides based on pepcans and morphiceptin (YPFP-NH2). Here, we combined injections of pepcans and morphiceptin to investigate the combination treatment of opioids and cannabis and compared the analgesic effect with chimeric compounds. Subsequently, we employed computational docking to screen the compounds against opioid and cannabinoid receptors, along with an acute pain model, to identify the most promising peptide. Among these peptides, MP-13, a morphiceptin and pepcan-9 (PVNFKLLSH) construct, exhibited superior supraspinal analgesic efficacy in the tail-flick test, with an ED50 value at 1.43 nmol/mouse, outperforming its parent peptides and other chimeric analogs. Additionally, MP-13 displayed potent analgesic activity mediated by mu-opioid receptor (MOR), delta-opioid receptor (DOR), and cannabinoid type 1 (CB1) receptor pathways. Furthermore, MP-13 did not induce psychological dependence and gastrointestinal motility inhibition at the effective analgesic doses, and it maintained non-tolerance-forming antinociception throughout a 7-day treatment regimen, with an unaltered count of microglial cells in the periaqueductal gray region, supporting this observation. Moreover, intracerebroventricular administration of MP-13 demonstrated dose-dependent antinociception in murine models of neuropathic, inflammatory, and visceral pain. Our findings provide promising insights for the development of opioid/cannabinoid peptide agonists, addressing a crucial gap in the field and holding significant potential for future research and development. PERSPECTIVE: This article offers insights into the combination treatment of pepcans with morphiceptin. Among the chimeric peptides, MP-13 exhibited potent analgesic effects in a series of preclinical pain models with a favorable side-effect profile.
