Binding of muscarinic ligands, both antagonists and agonists, and their effects on the conformation of the M2 acetylcholine receptor were modeled in silico and compared to experimental data. After docking of antagonists to the M2 receptor in an inactive conformation (3UON, 5ZK3, 5ZKB, or 5ZKB) and agonists in an active conformation (4MQS), 100 ns of conventional molecular dynamics (MD) followed by 500 ns of accelerated MD was run. Conventional MD revealed ligand-specific interactions with the receptor. Antagonists stabilized the receptor in an inactive conformation during accelerated MD. The receptor in complex with various agonists attained different conformations specific to individual agonists. The magnitude of the TM6 movement correlated with agonist efficacy at the non-preferential Gs pathway. The shape of the intracellular opening where the receptor interacts with a G-protein was different for the classical agonist carbachol, super-agonist iperoxo, and Gi/o-biased partial agonists JR-6 and JR-7, being compatible with experimentally observed agonist bias at the G-protein level. Moreover, a wash-resistant binding of the unique agonist xanomeline associated with interactions with membrane lipids was formed during accelerated MD. Thus, accelerated MD is suitable for modeling of ligand-specific receptor binding and receptor conformations that is essential for the design of experiments aimed at identification of the secondary binding sites and understanding molecular mechanisms underlying receptor activation.

Department of Experimental and Clinical Pharmacology University of Minnesota College of Pharmacy Minneapolis Minnesota 55455 United States

Department of Neurochemistry Institute of Physiology CAS Prague CZ 142 20 Czech Republic

Department of Physical Sciences Barry University Miami Shores Florida 33161 United States

References provided by Crossref.org

Agonist-selective activation of individual G-proteins by muscarinic receptors

A critical re-evaluation of the slope factor of the operational model of agonism: When to exponentiate operational efficacy