Identification Of Potential Natural Inhibitors Against Human Acetylcholinesterase Enzyme From Tubers Of Pueraria Tuberosa (Willd.): An Insilico Investigation
Keywords:
Acetylcholinesterase, Molecular Docking, Pueraria tuberosa, Deoxypodophyllotoxin, Tuberosin, cis-4-Decenedioic acid
Abstract
Human acetylcholinesterase enzyme acts as a key regulator of cholinergic signaling and its presence in post-synaptic membrane results in neuronal signal transmission termination via hydrolysis of neurotransmitter acetylcholine into acetate and choline. Acetylcholinesterase(AchE) inhibitors have proven therapeutic effect in neurodegenerative diseases like Alzheimer’s disease (AD) where AchE inhibitors could temporally compensate the cholinergic deficit by preventing acetylcholine hydrolysis and improving cholinergic transmission ultimately resulting in improved cognitive behaviour of AD patients. The present study aims to identify potential natural acetylcholinesterase(AchE) inhibitors from tubers of Pueraria tuberosa. Three-dimensional structure of human acetylcholinesterase enzyme (PDB ID: 7E3H) and 15 phytochemicals isolated from tubers of Pueraria tuberosa were downloaded from PDB and PubChem database, respectively. The pharmacological properties of phytochemicals were evaluated by the SwissADME tool to determine their Absorption, Distribution, Metabolism, and Excretion and Toxicity properties. The molecular docking interactions between acetylcholinesterase enzyme and phytochemicals were done using AutoDock Vina. Visualization of the docking complex was done in the Discovery Studio package. All phytochemicals exhibited strong binding with the Acetylcholinesterase as revealed by molecular docking analysis. Three compounds i.e, Deoxypodophyllotoxin, Tuberosin and cis-4-Decenedioic acid with a binding energy of -9.745,-9.733, and -6.8 kcal mol-1 are best suited candidate for devolvement as an Acetylcholinesterase inhibitor due to their high binding energies , Drug likeliness and favorable pharmacokinetics properties.References
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2. Cavallaro, V., Baier, C. J., Murray, M. G., Estévez-Braun, A., & Murray, A. P. (2018). Neuroprotective effects of Flaveria bidentis and Lippia salsa extracts on SH-SY5Y cells. South African Journal of Botany, 119, 318–324. https://doi.org/10.1016/j.sajb.2018.10.006
3. Dileep, K. V., Ihara, K., Mishima-Tsumagari, C., Kukimoto-Niino, M., Yonemochi, M., Hanada, K., Shirouzu, M., & Zhang, K. Y. J. (2022). Crystal structure of human acetylcholinesterase in complex with tacrine: Implications for drug discovery. International Journal of Biological Macromolecules, 210, 172–181. https://doi.org/10.1016/J.IJBIOMAC.2022.05.009
4. Jamali-Raeufy, N., Baluchnejadmojarad, T., Roghani, M., keimasi, S., & goudarzi, M. (2019). Isorhamnetin exerts neuroprotective effects in STZ-induced diabetic rats via attenuation of oxidative stress, inflammation and apoptosis. Journal of Chemical Neuroanatomy, 102, 101709. https://doi.org/10.1016/j.jchemneu.2019.101709
5. Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 46(1–3), 3–26. https://doi.org/10.1016/S0169-409X(00)00129-0
6. Sakkiah, S., Thangapandian, S., & Lee, K. W. (2012). Ligand-Based Virtual Screening and Molecular Docking Studies to Identify the Critical Chemical Features of Potent Cathepsin D Inhibitors. Chemical Biology & Drug Design, 80(1), 64–79. https://doi.org/10.1111/j.1747-0285.2012.01339.x
7. Singh, S. P., & Gupta, D. (2017). Discovery of potential inhibitor against human acetylcholinesterase: a molecular docking and molecular dynamics investigation. Computational Biology and Chemistry, 68, 224–230. https://doi.org/10.1016/J.COMPBIOLCHEM.2017.04.002
8. Tang, H., Song, P., Li, J., & Zhao, D. (2019). Effect of Salvia miltiorrhiza on acetylcholinesterase: Enzyme kinetics and interaction mechanism merging with molecular docking analysis. International Journal of Biological Macromolecules, 135, 303–313. https://doi.org/10.1016/J.IJBIOMAC.2019.05.132
9. Xu, P., Wang, K., Lu, C., Dong, L., Gao, L., Yan, M., Aibai, S., Yang, Y., & Liu, X. (2017). Protective effects of linalool against amyloid beta-induced cognitive deficits and damages in mice. Life Sciences, 174, 21–27. https://doi.org/10.1016/j.lfs.2017.02.010
10. Ghose, A.,Viswanadhan, V.,Wendoloski, J.(1999). A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. Journal of Combinatorial Chemistry, 1, 55-68.
11. Muegge, I., Heald, S.,Brittelli,D.(2001). Simple selection criteria for drug-like chemical matter. Journal of medicinal chemistry, 44(12),1841-1846.
Published
2022-02-22
How to Cite
Anami Ahuja, Sheetal Bhatia, & Pankaj Kumar Tyagi. (2022). Identification Of Potential Natural Inhibitors Against Human Acetylcholinesterase Enzyme From Tubers Of Pueraria Tuberosa (Willd.): An Insilico Investigation. Revista Electronica De Veterinaria, 83 -94. Retrieved from https://veterinaria.org/index.php/REDVET/article/view/1265
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