Discovery of novel PDE9A inhibitors with antioxidant activities for treatment of Alzheimer's disease

J Enzyme Inhib Med Chem. 2018 Dec;33(1):260-270. doi: 10.1080/14756366.2017.1412315.

Abstract

Phosphodiesterase-9 (PDE9) is a promising target for treatment of Alzheimer's disease (AD). To discover multifunctional anti-AD agents with capability of PDE9 inhibition and antioxidant activity, a series of novel pyrazolopyrimidinone derivatives, coupling with the pharmacophore of antioxidants such as ferulic and lipolic acids have been designed with the assistance of molecular docking and dynamics simulations. Twelve out of 14 synthesised compounds inhibited PDE9A with IC50 below 200 nM, and showed good antioxidant capacities in the ORAC assay. Compound 1h, the most promising multifunctional anti-AD agent, had IC50 of 56 nM against PDE9A and good antioxidant ability (ORAC (trolox) = 3.3). The selectivity of 1h over other PDEs was acceptable. In addition, 1h showed no cytotoxicity to human neuroblastoma SH-SY5Y cells. The analysis on structure-activity relationship (SAR) and binding modes of the compounds may provide insight into further modification.

Keywords: Alzheimer’s disease; Phosphodiesterase-9; antioxidant activity; molecular docking; multifunctional anti-AD agents.

MeSH terms

  • 3',5'-Cyclic-AMP Phosphodiesterases / antagonists & inhibitors*
  • 3',5'-Cyclic-AMP Phosphodiesterases / metabolism
  • Alzheimer Disease / drug therapy*
  • Alzheimer Disease / enzymology*
  • Antioxidants / chemical synthesis
  • Antioxidants / chemistry
  • Antioxidants / pharmacology*
  • Cell Line, Tumor
  • Dose-Response Relationship, Drug
  • Drug Discovery*
  • Humans
  • Models, Molecular
  • Molecular Structure
  • Phosphodiesterase Inhibitors / chemical synthesis
  • Phosphodiesterase Inhibitors / chemistry
  • Phosphodiesterase Inhibitors / pharmacology*
  • Structure-Activity Relationship

Substances

  • Antioxidants
  • Phosphodiesterase Inhibitors
  • 3',5'-Cyclic-AMP Phosphodiesterases
  • PDE9A protein, human

Grants and funding

This work was supported by the Natural Science Foundation of China (81522041, 81373258, 21572279, 21402243 and 81602968), Science Foundation of Guangdong Province (2014A020210009, 2016A030310144), Guangdong Province Higher Vocational Colleges & Schools Pearl River Scholar Funded Scheme (2016), Foundation of Traditional Chinese medicine Bureau of Guangdong Province (20171049) and State Key Laboratory for Chemistry and Molecular Engineering of Medicinal Resources (CMEMR2016-B03). We thank Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund (the second phase) under Grant No.U1501501 for providing the supercomputing service.