Molecular modeling of opioid receptor-ligand complexes

DARK Classics in Chemical Neuroscience: Fentanyl

Fentanyl rose to prominence as an alternative analgesic to morphine nearly 50 years ago; today, fentanyl has re-emerged as a dangerous recreational substance. The increased potency and analgesic effect of fentanyl are advantageous in the treatment of pain but are also responsible for the rise in unintentional opioid overdose deaths. In response to this crisis, fentanyl, its analogues, and even precursors are under heightened regulatory scrutiny. Despite this controversial history, derivatization of fentanyl has resulted in numerous synthetic analogues that provide valuable insights into opioid receptor binding and signaling events. In this review, the impact of fentanyl on chemical neuroscience is shown through its synthesis and properties, manufacturing, metabolism, pharmacology, approved and off-label indications, adverse effects, and the responsibility it has in the opioid epidemic.

A unique binding epitope for salvinorin A, a non-nitrogenous kappa opioid receptor agonist

Salvinorin A is a potent kappa opioid receptor (KOP) agonist with unique structural and pharmacological properties. This non-nitrogenous ligand lacks nearly all the structural features commonly associated with opioid ligand binding and selectivity. This study explores the structural basis to salvinorin A binding and selectivity using a combination of chimeric and single-point mutant opioid receptors. The experiments were designed based on previous models of salvinorin A that locate the ligand within a pocket formed by transmembrane (TM) II, VI, and VII. More traditional sites of opioid recognition were also explored, including the highly conserved aspartate in TM III (D138) and the KOP selectivity site E297, to determine the role, if any, that these residues play in binding and selectivity. The results indicate that salvinorin A recognizes a cluster of residues in TM II and VII, including Q115, Y119, Y312, Y313, and Y320. Based on the position of these residues within the receptor, and prior study on salvinorin A, a model is proposed that aligns the ligand vertically, between TM II and VII. In this orientation, the ligand spans residues that are spaced one to two turns down the face of the helices within the receptor cavity. The ligand is also in close proximity to EL-2 which, based on chimeric data, is proposed to play an indirect role in salvinorin A binding and selectivity.

Steric interactions and the activity of fentanyl analogs at the μ-opioid receptor

Fentanyl is a highly potent and clinically widely used narcotic analgesic. The synthesis of its analogs remains a challenge in the attempt to develop highly selective mu-opioid receptor agonists with specific pharmacological properties. In this paper, the use of flexible molecular docking in a study of the formation of complexes between a series of active fentanyl analogs and the mu-opioid receptor is described. The optimal position and orientation of fourteen fentanyl analogs in the binding pocket of the mu-receptor were determined. The major receptor amino acids and the ligand functional groups participating in the complex formation were identified. Stereochemical effects on the potency and binding are explained. The proposed model of ligand-receptor binding is in agreement with point mutation experiments explaining the role of the amino acids: Asp147, Tyr148, Asn230, His297, Trp318, His319, Cys321, and Tyr326 in the complex formation. In addition, the following amino acids were identified as being important for ligand binding or receptor activation: Ile322, Gly325, Val300, Met203, Leu200, Val143, and Ile144.

Engineering and functional immobilization of opioid receptors

Opioid receptors, like many G protein-coupled receptors (GPCRs), are notoriously unstable in detergents. We have now developed a more stable variant of the mu-opioid receptor (MOR) and also a method for the immobilization of solubilized, functional opioid receptors on a solid phase (magnetic beads). Starting with the intrinsically more stable kappa-opioid receptor (KOR), we optimized the conditions (i.e. detergents and stabilizing ligands) for receptor extraction from lipid bilayers of HEK293T cells to obtain maximal amounts of functional, immobilized receptor. After immobilization, the ligand binding profile remains the same as observed for the membrane-embedded receptor. For the immobilized wild-type mu-opioid receptor, however, no conditions were found under which ligand binding capacity was retained. To solve this problem, we engineered the receptor chimera KKM where the N-terminus and the first transmembrane helix (TM1) of wild-type MOR is exchanged for the homologous receptor parts of the wild-type KOR. This hybrid receptor behaves exactly as the wild-type MOR in functional assays. Interestingly, the modified MOR is expressed at six times higher levels than wild-type MOR and is similarly stable as wild-type KOR after immobilization. Hence the immobilized MOR, represented by the chimera KKM, is now also amenable for biophysical characterization. These results are encouraging for future stability engineering of GPCRs.

Modeling and simulation of the human delta opioid receptor

A model for the human delta opioid receptor has been generated via sequence alignment, structure building using the crystal structure of bovine rhodopsin as a template, and refinement by molecular dynamics simulation. The model building suggested that, in addition to the previously postulated interaction between D128 and Y308, an internal salt bridge also exists between residues D128 and R192, both of which are conserved in all the opioid receptors. The model and salt bridge were then shown to be stable during a 20-nsec simulation in a lipid bilayer. It is therefore proposed that both of these interactions play a role in stabilizing the inactive state of the receptor. The model is also used in an effort to rationalize many of the mutational studies performed on delta opioid receptors, and to suggest a plausible explanation for the differences between known delta opioid agonists and antagonists.