02897nas a2200265 4500008004100000245011800041210006900159260001500228300001200243490000700255520201000262653002302272653002602295653002802321653001702349653002202366653003402388653001502422100002802437700002702465700002702492700002602519700002702545856005902572 2024 eng d00aIn silico and Biological Screening of Phytochemicals against NMDA Receptor for Alzheimer’s Disease Therapeutics0 aIn silico and Biological Screening of Phytochemicals against NMD cApril 2024 a244-2530 v163 a

Background: Alzheimer's Disease (AD), characterized by irreversible neurodegeneration and cognitive decline, lacks a definitive cure, and current medications merely alleviate symptoms. Cognitive manifestations in AD are linked to disrupted glutamatergic neurotransmission, where β-Amyloid (A) accumulation at specific synapses interacts with glutamine synthetase, causing enzyme inactivation and subsequent NMDA signalling impairment. Dysregulation of glutamine synthetase leads to NMDA receptor hyper activation, resulting in neuronal damage and cell death. Aim: The focus of this investigation is on N-Methyl D-Aspartate (NMDA) receptors, which belong to the ionotropic glutamate receptor family and play vital roles in various physiological and pathological processes such as neuron development, synaptic plasticity, and central nervous system learning and memory. This study seeks to analyze target data to differentiate between effective and ineffective options for virtual screening. Utilizing this information, the study aims to generate a novel or enhanced reaction product. Materials and Methods: Computational embedding was employed to explore interactions between NMDA receptors and phytoconstituents of selected plants, including Amla, Shankhapushpi, Giloy, Ashwagandha, and Turmeric. ADMET descriptions for well-known botanical compounds were also scrutinized. Results: Structural analysis of 75 compounds derived from selected phytochemicals was conducted based on molecular properties. Key compounds were identified, and additional ADMET properties were evaluated. Quercetin emerged as the top-ranking compound based on shear score, shear strength, and molecular interactions with NMDA receptors. Conclusion: This computational study identifies specific plants as potential NMDA receptor antagonists, offering promise for mitigating Alzheimer's disease symptoms in the future.

10aADMET descriptions10aAlzheimer’s disease10aComputational embedding10aDock ligands10aMolecular docking10aN-methyl-D-aspartate-receptor10aQuercetin.1 aBaviskar, Bhushan, Arun1 aDeore, Sharada, Laxman1 aShende, Bhavana, Ashok1 aKhadabadi, Somshekhar1 aKide, Anjali, Ashokrao uhttps://phcogres.com/article/2024/16/2/105530pres16231