Targeting NMDA receptor in Alzheimer's disease: identifying novel inhibitors using computational approaches

• Published in: Frontiers in pharmacology 2023-06, Vol.14, p.1208968-1208968
• Main Authors: Siddiqui, Arif Jamal, Badraoui, Riadh, Jahan, Sadaf, Alshahrani, Mohammed Merae, Siddiqui, Maqsood Ahmed, Khan, Andleeb, Adnan, Mohd
• Format: Article
• Language: English
• Subjects: Alzheimer’s; computer biology; dynamics; free energy calculation; NMDA receptor; Pharmacology; pharmacophore
• ISSN: 1663-9812; 1663-9812
• DOI: 10.3389/fphar.2023.1208968

The glutamate-gated ion channels known as N-methyl-d-aspartate receptors (NMDARs) are important for both normal and pathological brain function. Subunit-selective antagonists have high therapeutic promise since many pathological conditions involve NMDAR over activation, although few clinical successes have been reported. Allosteric inhibitors of GluN2B-containing receptors are among the most potential NMDAR targeting drugs. Since the discovery of ifenprodil, a variety of GluN2B-selective compounds have been discovered, each with remarkably unique structural motifs. These results expand the allosteric and pharmacolog-ical spectrum of NMDARs and provide a new structural basis for the development of next-generation GluN2B antagonists that have therapeutic potential in brain diseases. Small molecule therapeutic inhibitors targeting NMDA have recently been developed to target CNS disorders such as Alzheimer's disease. In the current study, a cheminformatics method was used to discover potential antagonists and to identify the structural requirements for Gly/NMDA antagonism. In this case we have created a useful pharmacophore model with solid statistical values. Through pharmacophore mapping, the verified model was used to filter out virtual matches from the ZINC database. Assessing receptor-ligand binding mechanisms and affinities used molecular docking. To find the best hits, the GlideScore and the interaction of molecules with important amino acids were considered essential features. We found some molecular inhibitors, namely, ZINC13729211, ZINC07430424, ZINC08614951, ZINC60927204, ZINC12447511, and ZINC18889258 with high binding affinity using computational methods. The molecules in our studies showed characteristics such as good stability, hydrogen bonding and higher binding affinities in the solvation-based assessment method than ifenprodil with acceptable ADMET profile. Moreover, these six leads have been proposed as potential new perspectives for exploring potent Gly/NMDA receptor antagonists. In addition, it can be tested in the laboratory for potential therapeutic strategies for both and research.