In Vitro, In Vivo and In Silico Characterization of a Novel Kappa-Opioid Receptor Antagonist

Abstract

Kappa-opioid receptor (KOR) antagonists are promising innovative therapeutics for the treatment of the central nervous system (CNS) disorders. The new scaffold opioid ligand, Compound A, was originally found as a mu-opioid receptor (MOR) antagonist but its binding/selectivity and activation profile at the KOR and delta-opioid receptor (DOR) remain elusive. In this study, we present an in vitro, in vivo and in silico characterization of Compound A by revealing this ligand as a KOR antagonist in vitro and in vivo. In the radioligand competitive binding assay, Compound A bound at the human KOR, albeit with moderate affinity, but with increased affinity than to the human MOR and without specific binding at the human DOR, thus displaying a preferential KOR selectivity profile. Following subcutaneous administration in mice, Compound A effectively reverse the antinociceptive effects of the prototypical KOR agonist, U50,488. In silico investigations were carried out to assess the structural determinants responsible for opioid receptor subtype selectivity of Compound A. Molecular docking, molecular dynamics simulations and dynamic pharmacophore (dynophore) generation revealed differences in the stabilization of the chlorophenyl moiety of Compound A within the opioid receptor binding pockets, rationalizing the experimentally determined binding affinity values. This new chemotype bears the potential for favorable ADMET properties and holds promise for chemical optimization toward the development of potential therapeutics.

Multi-Level Biological Network Analysis and Drug Repurposing Based on Leukocyte Transcriptomics in Severe COVID-19: In Silico Systems Biology to Precision Medicine

“…In the bioinformatics and precision medicine era, systems biology and multi-omics studies allow translational medicine to be effective in clinical practices [ 35 ]. Several combined wet and dry experimental studies have provided invaluable information in molecular biology and medicine [ 36 , 37 , 38 ]. Moreover, a combination of knowledge between biology, computer science, statistics, and mathematics explores the underlying molecular mechanisms of numerous diseases such as cancer, degenerative diseases, genetic diseases, etc.…”

Design and structural validation of peptide–drug conjugate ligands of the kappa-opioid receptor

“…For the antagonism study, nor-BNI (13.6 µmol kg −1 ) was s.c. administered 24 h before DNCP-β-NalA(1) (3.8 µmol kg −1 ) and pain behavior was assessed as described above. Antinociceptive activity in the formalin test, as percentage decrease in duration of pain behavior compared to the saline (control) group, was calculated according to the following formula: 100*½ CÀT C , where C is the mean time in control (saline) group and T is the time in drugtreated group 82 . Dose-response relationships of percentage inhibition of pain behavior were constructed, and the dose necessary to produce a 50% effect (ED 50 ) and 95% confidence limits (95% CL) was calculated according to the method of Litchfield and Wilcoxon 83 .…”

Recent Advances in the Synthesis and Applications of m-Aryloxy Phenols

“…This compound showed strong antagonistic properties at the κ opioid receptor, with inhibition agonist-stimulated [35S]GTPγS binding in cloned human μ (DAMGO) -Ke(nM)a = 69 ± 14, δ (DPDPE) − Ke(nM)a = 625 ± 120, and κ (U69,593) − Ke(nM)a = 1.85 ± 0.51. The authors believed these compounds will be useful in the development of clinical candidates for treating conditions such as depression, anxiety, schizophrenia, and addictions, as well as serving as pharmacological tools [ 9 , 10 , 11 ].…”