Analysis of the Glutamate Agonist LY404,039 Binding to Nonstatic Dopamine Receptor D2 Dimer Structures and Consensus Docking


Salmas R. E., Seeman P., Aksoydan B., Erol I., Kantarcioglu I., Stein M., ...Daha Fazla

ACS CHEMICAL NEUROSCIENCE, cilt.8, sa.6, ss.1404-1415, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8 Sayı: 6
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1021/acschemneuro.7b00070
  • Dergi Adı: ACS CHEMICAL NEUROSCIENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1404-1415
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Dopamine receptor D2 (D2R) plays an important role in the human central nervous system and is a focal target of antipsychotic agents. The D2(High)R and D2(Low)R dimeric models previously developed by our group are used to investigate the prediction of binding affinity of the LY404,039 ligand and its binding mechanism within the catalytic domain. The computational data obtained using molecular dynamics simulations fit well with the experimental results. The calculated binding affinities of LY404,039 using MM/PBSA for the D2(High)R and D2(Low)R targets were -12.04 and -9.11 kcal/mol, respectively. The experimental results suggest that LY404,039 binds to D2(High)R and D2L(ow)R with binding affinities (K-i) of 8.2 and 1640 nM, respectively. The high binding affinity of LY404,039 in terms of binding to [H-3]domperidone was inhibited by the presence of a guanine nucleotide, indicating an agonist action of the drug at D2(High)R. The interaction analysis demonstrated that while Asp114 was among the most critical amino acids for D2(High)R binding, residues Ser193 and Ser197 were significantly more important within the binding cavity of D2(Low)R Molecular modeling analyses are extended to ensemble docking as well as structure-based pharmacophore model (E-pharmacophore) development using the bioactive conformation of LY404,039 at the binding pocket as a template and screening of small-molecule databases with derived pharmacophore models.