In silico identification of novel 5-HT_2A antagonists supported with ligand- and target-based drug design methodologies

Abstract

A wide range of neuropsychological disorders is caused by serotonin 5-HT_2A receptor (5-HT_2AR) malfunction. Therefore, this receptor had been frequently used as target in CNS drug research. To design novel potent 5-HT_2AR 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-HT_2A receptor, we have obtained virtually bioactive conformations of the ligands and three different antagonist-bound, inactive, conformations of the 5-HT_2AR. These three 5-HT_2AR 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-HT_2A 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-HT_2AR antagonists.

Communicated by Ramaswamy H. Sarma

Keywords:

• 5-HT2A
• 3D-QSAR
• pharmacophore modelling
• molecular docking
• molecular dynamics simulations

Acknowledgements

This research was supported by Serbian Ministry of Education, Science and Technological Development, national project No. 172033. Numerical simulations were run on the PARADOX-IV supercomputing facility at the Scientific Computing Laboratory, National Center of Excellence for the Study of Complex Systems, Institute of Physics Belgrade, supported in part by the Ministry of Education, Science, and Technological Development of the Republic of Serbia under project No. ON171017. We acknowledge project of Ministry of Science and Technological Development of the Republic of Serbia. Finally, we thank Horison 2020/COST action CA18133 “European Research Network on Signal Transduction” for support.