Design, synthesis and molecular modelling of new bulky Fananserin derivatives with altered pharmacological profile as potential antidepressants

Abstract

It is now known that many neurotransmitter systems are responsible for diseases of the central nervous system (CNS). One of the most common CNS disease is depression. Considering that in the treatment and the genesis of depression, the most important are the serotonin receptors from 5-HT1A, 5-HT2A, 5-HT6 and 5-HT7 groups, and dopamine D2R this article describes searching for group of new ligands for mentioned receptors. In the searching for potentially useful compound, we decided to start from the structure of well-known Fananserin. We tried to developed new derivatives, with changed profile of activity compared to Fananserin. Literature analysis and virtual screening emerged group of halogenated long-chain arylpiperazines derivatives of 1,8 naphthosultam/lactam with hexyl carbon chain to synthesis. The compounds obtaining method was developed with a microwave assisted synthesis. Reactions were carried out in acetonitrile, water or in solvent-free conditions. The obtained compounds were tested for their affinity for the serotonin receptors mentioned above. The work managed to obtain compounds acting on selected serotonin receptors, including multifunctional 5-HT1A/5-HT7/D2 ligand 5k, dual 5-HT1A/D2 ligand 5j and selective 5-HT1A ligands 5r and 5c. The SAR analysis showed a visible dependence of affinity for the 5-HT6 receptors from structure of ligands. This relationship was discussed using molecular docking methods. A conformal analysis was also performed for selected ligands and the Fukui indexes were calculated using the DFT (B3LYP/6-311+G (d,p) level of theory) methods. The conducted research and analysis using molecular docking methods allows for selecting further pathways of structural modifications in the design of new ligands for serotonin receptors belonging to the group mentioned. What is more, conducted research show the potential using of Fukui indices to predict the biological activity of new molecules.