Identification of novel and structurally diverse N-Methyl-D-Aspartate Receptor Antagonists: Successful Application of Pharmacophore Modeling, Virtual Screening and Molecular Docking

Abstract

In view of "excitotoxic" effects of glutamate, wherein excessive excitatory input causes increase in intracellular Ca 2+ and ultimately cell death, NMDA receptor has emerged as an important target for treatment and prevention of several neurological disorders, like Alzheimer disease.Prompted by the successful application of in-silico pharmacophore-based virtual screening in lead identification, we have made an effort to implement in-silico protocols to identify novel NMDA receptor antagonist. A series of novel benzo[b]quinolizinium cations as NMDA receptor antagonists have been used as a starting point to develop prognostic pharmacophore models. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, one hydrogen bond acceptor, one hydrophobic and two ring aromatic, showed a correlation (r) of 0.89, root mean square of 0.259, and the cost difference of 43.01 bits between null and fixed cost. The model was thoroughly validated and subjected to a chemical database search, which lead to the identification of 400 hits from NCI and Maybridge databases which were checked for Lipinski's violation and predictive potency. This reduced the list to 10 compounds, out of which, two most potent compounds were subjected to molecular docking using Libdock software and interestingly, all the docked conformations showed hydrogen bond interactions with important amino acids Tyr214, His88, Thr174, Val169 and Arg121. In summary, through our validated pharmacophore-based virtual screening protocol, we have identified two potent, structurally diverse, druggable and novel NMDA receptor antagonist which might be of great help to address the unmet medical need of Alzheimer disease.

Pharmacophore-driven Identification of N-Methyl-D-Receptor Antagonists as Potent Neuroprotective Agents Validated UsingIn-VivoStudies

“…The lead compounds with good fit values, estimated activity, drug-likeness and docking score are checked for novelty by employing pairwise tanimoto similarity indices using “Find Similar Molecules by Fingerprint” protocol in Discovery Studio. In this study, all the lead compounds show low Tanimoto similarity indices to all the structures of known NMDA receptors antagonists validating their uniqueness 7 . The third phase entails molecular docking studies succeeded by evaluating the retrieved potent lead compounds for neuroprotective activity.…”

Pharmacophore-driven identification of N-methyl-D-receptor antagonists as potent neuroprotective agents validated using in vivo studies

“…To understand the nature of molecular interactions of the lead compounds, we carried out molecular docking studies using DS [ 37 , 38 ]. LibDocker, a molecular dynamics annealing-based algorithm, which is accessible as an extension of DS V.2.0, was used for the docking studies [ 39 , 40 ]. The crystal structures to be used for docking studies were obtained from PDB.…”