A structural feature of the non-peptide ligand interactions with mice mu-opioid receptors

By binding to and activating the G-protein coupled μ-, κ- and δ-opioid receptors in the central nervous system, opiates are known to induce analgesic and sedative effects. In particular, non-peptide opioid ligands are often used in clinical applications to induce these therapeutically beneficial effects, due to their superior pharmacokinetics and bioavailability in comparison to endogenous neuropeptides. However, since opioid alkaloids are highly addictive substances, it is necessary to understand the exact mechanisms of their actions, specifically the ligand-binding properties of the target receptors, in order to safely apply opiates for therapeutic purposes. Using an in silico molecular docking approach (AutoDock Vina) combined with two-step cluster analysis, we have computationally obtained the docking scores and the ligand-binding pockets of twelve representative non-peptide nonendogenous agonists and antagonists at the crystallographically identified μ-opioid receptor. Our study predicts the existence of two main binding sites that are congruently present in all opioid receptor types. Interestingly, in terms of the agonist or antagonist properties of the substances on the receptors, the clustering analysis suggests a relationship with the position of the ligand-binding pockets, particularly its depth within the receptor structure. Furthermore, the binding affinity of the substances is directly correlated to the proximity of the binding pockets to the extracellular space. In conclusion, the results provide further insights into the structural features of the functional pharmacology of opioid receptors, suggesting the importance of the binding position of non-peptide agonists and antagonists- specifically the distance and the level of exposure to the extracellular space- to their dissociation kinetics and subsequent potency.

Medienart:

E-Artikel

Erscheinungsjahr:

2014

Erschienen:

2014

Enthalten in:

Zur Gesamtaufnahme - volume:10

Enthalten in:

Current computer-aided drug design - 10(2014), 4 vom: 11., Seite 354-60

Sprache:

Englisch

Beteiligte Personen:

Noori, Hamid R [VerfasserIn]
Mucksch, Christian [VerfasserIn]
Urbassek, Herbert M [VerfasserIn]

Themen:

Analgesics, Opioid
Journal Article
Ligands
Receptors, Opioid, mu
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 16.11.2015

Date Revised 13.11.2019

published: Print

Citation Status MEDLINE

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM243196555