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ORIGINAL ARTICLE
Year : 2018  |  Volume : 14  |  Issue : 59  |  Page : 638-642

In silico analysis of binding interaction of phytoconstituents with N-methyl-D-aspartate receptor for potential therapeutic use in Alzheimer's disease


University School of Biotechnology, Guru Gobind Singh Indraprastha University, Dwarka, New Delhi, India

Correspondence Address:
Suresh Kumar
University School of Biotechnology, Guru Gobind Singh Indraprastha University, New Delhi - 110 075
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/pm.pm_214_18

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Background: Alzheimer's disease (AD) is an irreversible neurodegenerative disease associated with memory loss and cognition deficit. At present, the drugs which are available in the markets only provide symptomatic relief to patients; there is no permanent cure for this disease. Several hypotheses have been proposed by various researchers, one of them is glutamatergic hypothesis which states the involvement of glutamate-mediated neurotoxicity in the pathogenesis of AD. The dysfunctional glutamine synthetase leads to overactivation of N-methyl-D-aspartate (NMDA) receptor resulting in neuronal injury and cell death. Objective: The present study was aimed to identify potential phytoconstituents as NMDA-receptor antagonist from conventionally used Indian spices for treating AD. Materials and Methods: In silico docking was performed to study the molecular interaction of different phytoconstituent from selected traditional spices such as clove, cumin, green cardamom, cinnamon, and black pepper, against NMDA receptor. ADMET descriptors were also determined for the top hit phytoconstituent. Results: Structure-based screening of 250 compounds from selected spices was performed on the basis of molecular docking. The top five leads were selected and further evaluated for ADMET properties. Caffeic acid was top lead based on the glide score, glide energy, and molecular interaction with NMDA receptor. Conclusion: The present study establishes different phytoconstituents as potential NMDA-receptor antagonist by in silico approach which can be useful in future as potential lead for the alleviation of symptoms associated with Alzheimer's disease. Abbreviations Used: AD: Alzheimer's Disease; NMDA: N-Methyl-D-Aspartate; ADMET: Absorption, Distribution, Metabolism, Excretion and Toxicity; CNS: Central Nervous System; Ca2+: Calcium ion; Amyloid Beta (Aβ); FDA: United States Food and Drug Administration; RCSB: Research Collaboratory for Structural Bioinformatics; PDB: Protein Data Bank; DCKA: 5,7-Dichlorokynurenic acid; NCBI: National Center for Biotechnology; Glide: Grid based Ligand Docking with Energetics; OPLS: Optimized Potentials for Liquid Simulations; BBB: Blood Brain Barrier; HIA: Intestinal Absorption; donorHB: Hydrogen bond donors; accptHB: Hydrogen bond acceptors; QPlogPo/w: Predicted octanol/water partition coefficient; RMSD: Root mean square deviation; Glu/NMDA: Glutamate binding site; Gly/NMDA: Glycine binding site; PC12: Pheochromocytoma cells of Rat adrenal medulla.


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