2017
DOI: 10.1016/j.bmcl.2017.08.025
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Design, synthesis, and biological activity of 5′-phenyl-1,2,5,6-tetrahydro-3,3′-bipyridine analogues as potential antagonists of nicotinic acetylcholine receptors

Abstract: Starting from a known non-specific agonist (1) of nicotinic acetylcholine receptors (nAChRs), rationally guided structural-based design resulted in the discovery of a small series of 5′-phenyl-1,2,5,6-tetrahydro-3,3′-bipyridines (3a – 3e) incorporating a phenyl ring off the pyridine core of 1. The compounds were synthesized via successive Suzuki couplings on a suitably functionalized pyridine starting monomer 4 to append phenyl and pyridyl substituents off the 3- and 5-positions, respectively, and then make su… Show more

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Cited by 2 publications
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“…Recent advancement in computational power and support for GPU-accelerated hardware have made long-time scale MD simulations (0.1–1 μs) more feasible for large-scale systems, including lipid bilayers with proteins embedded within them . Through a combination of the MD simulations and molecular mechanics–Poisson–Boltzmann surface area (MM-PBSA) binding free energy calculations, compounds binding with a given protein can be ranked accurately in correlation with their experimental binding free energy (Δ G exp ) values. , Our group has previously been successful in developing and utilizing various computational approaches for modeling ligands binding with the transmembrane proteins to elucidate subtype selectivity. Hence, in the present study, we employed a variety of computational methods, including molecular docking, MD, and MM-PBSA, to explore the binding poses of these interesting compounds (Figures and ) with CB 1 R and CB 2 R and reveal the binding and selective mechanism. According to the computational data, the IQD series of compounds bind to the receptors in the known traditional binding site (phytocannabinoid binding site) of the receptors, whereas the long-chain cannabinoids bind to the receptors in a binding mode which is more favorable for CB 1 R. These computationally determined binding modes show excellent correlation with the empirically obtained binding data, suggesting that these binding modes are reasonable for these receptors.…”
Section: Introductionmentioning
confidence: 99%
“…Recent advancement in computational power and support for GPU-accelerated hardware have made long-time scale MD simulations (0.1–1 μs) more feasible for large-scale systems, including lipid bilayers with proteins embedded within them . Through a combination of the MD simulations and molecular mechanics–Poisson–Boltzmann surface area (MM-PBSA) binding free energy calculations, compounds binding with a given protein can be ranked accurately in correlation with their experimental binding free energy (Δ G exp ) values. , Our group has previously been successful in developing and utilizing various computational approaches for modeling ligands binding with the transmembrane proteins to elucidate subtype selectivity. Hence, in the present study, we employed a variety of computational methods, including molecular docking, MD, and MM-PBSA, to explore the binding poses of these interesting compounds (Figures and ) with CB 1 R and CB 2 R and reveal the binding and selective mechanism. According to the computational data, the IQD series of compounds bind to the receptors in the known traditional binding site (phytocannabinoid binding site) of the receptors, whereas the long-chain cannabinoids bind to the receptors in a binding mode which is more favorable for CB 1 R. These computationally determined binding modes show excellent correlation with the empirically obtained binding data, suggesting that these binding modes are reasonable for these receptors.…”
Section: Introductionmentioning
confidence: 99%