Harnessing the Anti-Nociceptive Potential of NK2 and NK3 Ligands in the Design of New Multifunctional μ/δ-Opioid Agonist–Neurokinin Antagonist Peptidomimetics

Opioid agonists are well-established analgesics, widely prescribed for acute but also chronic pain. However, their efficiency comes with the price of drastically impacting side effects that are inherently linked to their prolonged use. To answer these liabilities, designed multiple ligands (DMLs) offer a promising strategy by co-targeting opioid and non-opioid signaling pathways involved in nociception. Despite being intimately linked to the Substance P (SP)/neurokinin 1 (NK1) system, which is broadly examined for pain treatment, the neurokinin receptors NK2 and NK3 have so far been neglected in such DMLs. Herein, a series of newly designed opioid agonist-NK2 or -NK3 antagonists is reported. A selection of reported peptidic, pseudo-peptidic, and non-peptide neurokinin NK2 and NK3 ligands were covalently linked to the peptidic μ-opioid selective pharmacophore Dmt-DALDA (H-Dmt-d-Arg-Phe-Lys-NH2) and the dual μ/δ opioid agonist H-Dmt-d-Arg-Aba-βAla-NH2 (KGOP01). Opioid binding assays unequivocally demonstrated that only hybrids SBL-OPNK-5, SBL-OPNK-7 and SBL-OPNK-9, bearing the KGOP01 scaffold, conserved nanomolar range μ-opioid receptor (MOR) affinity, and slightly reduced affinity for the δ-opioid receptor (DOR). Moreover, NK binding experiments proved that compounds SBL-OPNK-5, SBL-OPNK-7, and SBL-OPNK-9 exhibited (sub)nanomolar binding affinity for NK2 and NK3, opening promising opportunities for the design of next-generation opioid hybrids.

Structure-Based Approach for the Prediction of Mu-opioid Binding Affinity of Unclassified Designer Fentanyl-Like Molecules

Three quantitative structure-activity relationship (QSAR) models for predicting the affinity of mu-opioid receptor (OR) ligands have been developed. The resulted models, exploiting the accessibility of the QSAR modeling, generate a useful tool for the investigation and identification of unclassified fentanyl-like structures. The models have been built using a set of 115 molecules using Forge as a software, and the quality was confirmed by statistical analysis, resulting in being effective for their predictive and descriptive capabilities. The three different approaches were then combined to produce a consensus model and were exploited to explore the chemical landscape of 3000 fentanyl-like structures, generated by a theoretical scaffold-hopping approach. The findings of this study should facilitate the identification and classification of new OR ligands with fentanyl-like structures.

Opioid-Induced Constipation: Pathophysiology, Clinical Consequences, and Management

Although opioids offer potent analgesia for severe acute and chronic noncancer pain, adverse gastrointestinal effects potentially undermine their clinical utility. In particular, between 40% and 95% of patients develop opioid-induced constipation (OIC). Therefore, there is a consensus that patients should commence laxatives at the start of opioid therapy and continue throughout treatment. Nevertheless, laxatives are not routinely coprescribed with opioids. Even when concurrent laxatives are prescribed, approximately half the patients treated for OIC do not achieve the desired improvement. Moreover, laxatives do not target the underlying cause of OIC (opioid binding to theμ-receptors in the enteric system) and as such are not very effective at managing OIC. The failure of lifestyle modification and laxatives to treat adequately many cases of OIC led to the concurrent use of peripherally acting opioid antagonists (such as methylnaltrexone bromide and naloxone) to reduce the incidence of gastrointestinal adverse events without compromising analgesia. Judicious use of the various options to manage OIC should allow more patients to benefit from opioid analgesia. Therefore, this paper reviews the causes, consequences, and management of OIC to help clinicians optimise opioid analgesia.