Abstract
Alzheimer’s disease (AD) is a chronic intensifying neurodegenerative disorder and accounts for three fourths of dementia cases. To date, there is no effective treatment available which can completely cure AD. The available medications can slower AD progression and can provide symptomatic relaxation. The N-methyl-d-aspartate receptor (NMDAR) plays a paramount role in the survival of neurons and synaptic plasticity. It is also involved in several other diseases. Although, excessive function of NMDAR cause excitotoxicity. Due to this the cell death process activated resulting into neurodegeneration and promotes AD. Hence in this study, we have screened 98,072 natural compounds using Smina and idock. After that top scoring 154 compounds were selected and ADMET analysis was carried out. It reveals that 18 compounds are good fit in all the ADMET parameters and employed for the re-docking studies using Autodock Vina. Then from the docking result, we have selected top three complexes (NMDAR-ZINC4258884, NMDAR-ZINC8635472, and NMDAR-ZINC15675934) and employed them for the 100 ns MDS studies. Based on MDS and Gibbs free energy landscape result analysis we have concluded that NMDAR-ZINC4258884 and NMDAR-ZINC15675934 are the best stable complex and can function as a lead compound against the NMDAR. Although this is a theoretical study while we have shortlisted only two compounds out of 98,072 compounds using rigorous computational approach and proposed them to the scientific community worldwide for further experimental validations.
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Acknowledgements
RS and TRS want to thanks the ICMR (ISRM/11(53)/2019) for providing the Senior Research Fellowship to RS.
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TRS conceived the study. GS and RS carried out all the experiments and the data analysis. GS, RS and TRS participated in its overall design and coordination of the study. The first draft of the manuscript was prepared by GS and RS. All authors read and approved the final manuscript.
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Sharma, G., Shukla, R. & Singh, T.R. Identification of small molecules against the NMDAR: an insight from virtual screening, density functional theory, free energy landscape and molecular dynamics simulation-based findings. Netw Model Anal Health Inform Bioinforma 11, 31 (2022). https://doi.org/10.1007/s13721-022-00374-2
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DOI: https://doi.org/10.1007/s13721-022-00374-2