Identification of potential dual histamine H3 receptor antagonist and serotonin reuptake inhibitors through ligand-based and structure-based approaches

Abstract

The major depressive disorder (MDD), routinely treated with selective serotonin reuptake inhibitors (SSRIs), is the second leading cause of disability worldwide. However, the treatment of MDD is complicated by high prevalence of residual symptoms connected to increased risk of relapse. Some of the most common residual symptoms are cognitive dysfunction and fatigue. Histamine H3 receptor (H3R) antagonists are both, pro-cognitive and wake-promoting agents. In pre-clinical study it was suggested that dual histamine H3R antagonist and SSRI may have utility as a more efficient antidepressant therapy. The aim of this in silico study was identification of novel dual SSRI/H3R antagonist using ligand-based and structure-based drug design techniques. Starting from structures and activities of known dual ligands, two GRIND-based 3D-QSAR models have been developed, SERT model (R2 = 0.97; Q2 = 0.79; SDEP= 0.124) and H3R model (R2 = 0.86; Q2 = 0.75; SDEP= 0.184), and 3Dpharmacophores were constructed. Further, homology model of H3R was built and refined with molecular dynamics. The hypotheses of binding modes for dual ligands were generated with molecular docking on H3R model and X-ray structure of SERT. In the second part of this study, ligand-based and structure-based virtual screening models were generated and validated. Prospective screening of ZINC database was performed in order to extract novel chemotypes of dual ligands. Final selection of ligands was performed based on generated pharmacophore and docking models as well as predicted pharmacokinetic properties. Few novel compounds were emphasized as promising starting point for development of new classes of dual antidepressants.