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In silico and in vitro studies of two non-imidazole multiple targeting agents at histamine H3 receptors and cholinesterase enzymes.

Nakisa GhamariSiavoush DastmalchiOmid ZareiJosé-Antonio Arias-MontañoDavid ReinerFulya Ustun AlkanHolger StarkMaryam Hamzeh-Mivehroud
Published in: Chemical biology & drug design (2019)
Recently, multi-target directed ligands have been of research interest for multifactorial disorders such as Alzheimer's disease (AD). Since H3 receptors (H3 Rs) and cholinesterases are involved in pathophysiology of AD, identification of dual-acting compounds capable of improving cholinergic neurotransmission is of importance in AD pharmacotherapy. In the present study, H3 R antagonistic activity combined with anticholinesterase properties of two previously computationally identified lead compounds, that is, compound 3 (6-chloro-N-methyl-N-[3-(4-methylpiperazin-1-yl)propyl]-1H-indole-2-carboxamide) and compound 4 (7-chloro-N-[(1-methylpiperidin-3-yl)methyl]-1,2,3,4-tetrahydroisoquinoline-2-carboxamide), was tested. Moreover, molecular docking and binding free energy calculations were conducted for binding mode and affinity prediction of studied ligands toward cholinesterases. Biological evaluations revealed inhibitory activity of ligands in nanomolar (compound 3: H3 R EC50  = 0.73 nM; compound 4: H3 R EC50  = 31 nM) and micromolar values (compound 3: AChE IC50  = 9.09 µM, BuChE IC50  = 21.10 µM; compound 4: AChE IC50  = 8.40 µM, BuChE IC50  = 4.93 µM) for H3 R antagonism and cholinesterase inhibition, respectively. Binding free energies yielded good consistency with cholinesterase inhibitory profiles. The results of this study can be used for lead optimization where dual inhibitory activity on H3 R and cholinesterases is needed. Such ligands can exert their biological activity in a synergistic manner resulting in higher potency and efficacy.
Keyphrases
  • molecular docking
  • molecular dynamics simulations
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  • binding protein
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  • drug delivery
  • single cell
  • mass spectrometry
  • solid state
  • bioinformatics analysis