In silico identification of novel 5-HT2A antagonists supported with ligand- and target-based drug design methodologies.
A wide range of neuropsychological disorders is caused by serotonin 5-HT2A receptor (5-HT2AR) malfunction. Therefore, this receptor had been frequently used as target in CNS drug research. To design novel potent 5-HT2AR antagonists, we have combined ligand-based and target-based approaches. This study was performed on wide range of structurally diverse antagonists that were divided into three different clusters: clozapine, ziprasidone, and ChEMBL240876 derivatives. By performing the 50 ns long molecular dynamic simulations with each cluster representative in complex with 5-HT2A receptor, we have obtained virtually bioactive conformations of the ligands and three different antagonist-bound, inactive, conformations of the 5-HT2AR. These three 5-HT2AR conformations were further used for docking studies and generation of the bioactive conformations of the data set ligands in each cluster. Subsequently, selected conformers were used for 3D-Quantitative Structure Activity Relationship (3D-QSAR) modelling and pharmacophore analysis. The reliability and predictive power of the created model was assessed using an external test set compounds and showed reasonable external predictability. Statistically significant variables were used to define the most important structural features required for 5-HT2A antagonistic activity. Conclusions obtained from performed ligand-based (3D-QSAR) and target-based (molecular docking and molecular dynamics) methods were compiled and used as guidelines for rational drug design of novel 5-HT2AR antagonists.Communicated by Ramaswamy H. Sarma.
['Radan|Milica|M|', 'Ruzic|Dusan|D|', 'Antonijevic|Mirjana|M|', 'Djikic|Teodora|T|', 'Nikolic|Katarina|K|']
D015195:Drug Design D008024:Ligands D062105:Molecular Docking Simulation D056004:Molecular Dynamics Simulation D021281:Quantitative Structure-Activity Relationship D015203:Reproducibility of Results D012701:Serotonin
5-HT2A molecular dynamics simulations 3D-QSAR molecular docking pharmacophore modelling