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Cholinesterase and Neurodegenerative Diseases · Journal article
The American Journal of Science and Medical Research · July 17, 2026
Raises a question worth testing. It does not answer one.
This in silico study used molecular docking to predict the binding affinity of eight phytochemicals to acetylcholinesterase, identifying 6,7-dimethoxy-4-phenylcoumarin as having the highest predicted affinity (−8.9 kcal/mol), comparable to the reference inhibitor donepezil. The work is exploratory computational modelling that does not establish biological activity or therapeutic potential and requires experimental validation.
Computational molecular docking simulation (in silico). Eight phytochemical compounds (no description of selection criteria, source, or chemical library); acetylcholinesterase enzyme structure from protein database; comparison to donepezil.. Intervention: Six phytochemicals other than 6,7-dimethoxy-4-phenylcoumarin (specific compounds not individually named in abstract).. Compared with: Donepezil (standard AChE inhibitor); 6,7-dimethoxy-4-phenylcoumarin as lead candidate..
6,7-Dimethoxy-4-phenylcoumarin showed highest binding energy of −8.9 kcal/mol against AChE Compound forms hydrogen bond with Tyr72 and hydrophobic interactions with Tyr341, Trp286, and Leu76 Binding energy and interaction pattern similar to standard inhibitor Donepezil
No in vitro or in vivo efficacy, safety, or toxicity data.
This computational prediction has no direct clinical implications until in vitro and in vivo validation is completed. Clinicians should not consider these findings as evidence for therapeutic use; this represents early-stage lead identification only.
This is a computational molecular docking study with no experimental validation, comparing phytochemical binding affinity to AChE in silico; it raises mechanistic questions but provides no evidence of biological activity or clinical relevance.
As stated by the source record.
Quoted from the source exactly as published.
This computational prediction has no direct clinical implications until in vitro and in vivo validation is completed. Clinicians should not consider these findings as evidence for therapeutic use; this represents early-stage lead identification only.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
ABSTRACT Alzheimer's disease is a progressive neurodegenerative disorder characterised by cognitive impairment and memory loss, primarily associated with the degeneration of cholinergic neurons. Inhibition of Acetylcholinesterase (AChE) is considered an effective therapeutic strategy to enhance cholinergic neurotransmission and alleviate the symptoms of the disease. In the present study, molecular docking simulations were performed to evaluate the inhibitory potential of eight selected phytochemicals against AChE. The docking analysis was conducted to investigate the binding affinity and interaction patterns of these compounds within the active site of the enzyme. Among the screened phytochemicals, 6,7-Dimethoxy-4-phenylcoumarin exhibited the highest binding affinity with a binding energy of −8.9 kcal/mol, indicating the formation of a stable enzyme–ligand complex. Detailed interaction analysis revealed that the compound forms a hydrogen bond interaction with Tyr72, along with significant hydrophobic interactions involving Tyr341, Trp286, and Leu76 within the active gorge of AChE. These residues play an important role in ligand stabilisation at the peripheral anionic site and within the aromatic gorge of the enzyme. The docking results were further compared with the standard AChE inhibitor Donepezil, which demonstrated a similar binding energy and interaction pattern with key active-site residues, including Tyr72, Trp286, Tyr341, Tyr337, and Val294. In addition to the top-ranked compound, the remaining seven phytochemicals also exhibited favourable binding affinities ranging from −7.3 to −8.9 kcal/mol, indicating significant interaction with the active site of AChE and suggesting their potential inhibitory activity. These findings highlight 6,7-Dimethoxy-4-phenylcoumarin and the other screened phytochemicals as promising natural inhibitors of AChE, which may serve as potential lead compounds for the development of alternative therapeutic agents for the management of Alzheimer's disease. However, further in vitro and in vivo studies are required to validate their pharmacological efficacy and safety. References [1] Ahmad, S., et al. (2021). Natural products as acetylcholinesterase inhibitors. Journal of Enzyme Inhibition and Medicinal Chemistry, 36(1), 1–27. [2] Bartus, R. T., Dean, R. L., Beer, B., & Lippa, A. S. (1982). The cholinergic hypothesis of geriatric memory dysfunction. Science, 217(4558), 408–414. [3] Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H.,.. & Bourne, P. E. (2000). The protein data bank. Nucleic acids research, 28(1), 235-242. [4] Birks, J. (2006). Cholinesterase inhibitors for Alzheimer’s disease. Cochrane Database of Systematic Reviews, CD005593. [5] Cheng, F., Li, W., Zhou, Y., Shen, J., Wu, Z., Liu, G., & Tang, Y. (2012). ADMET prediction. Journal of Chemical Information and Modeling, 52(11), 3099–3105. [6] Cheung, J., et al. (2012). Structures of human acetylcholinesterase. Journal of Medicinal Chemistry, 55(22), 10282–10286. [7] Cheung, J., Rudolph, M. J., Burshteyn, F., Cassidy, M. S., Gary, E. N., Love, J.,.. & Height, J. J. (2012). Structures of human acetylcholinesterase in complex with pharmacologically important ligands. Journal of medicinal chemistry, 55(22), 10282-10286. [8] Colovic, M. B., Krstic, D. Z., Lazarevic-Pasti, T. D., Bondzic, A. M., & Vasic, V. M. (2013). Acetylcholinesterase inhibitors: pharmacology and toxicology. Current Neuropharmacology, 11(3), 315–335. [9] Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME. Scientific Reports, 7, 42717. [10] Dey, A., Bhattacharya, R., Mukherjee, A., & Pandey, D. K. (2017). Natural products against Alzheimer’s disease. Phytotherapy Research, 31(12), 1906–1925. [11] Ferreira, L. G., dos Santos, R. N., Oliva, G., & Andricopulo, A. D. (2015). Molecular docking and structure-based drug design strategies. Molecules, 20(7), 13384–13421. [12] Francis, P. T., Palmer, A. M., Snape, M., & Wilcock, G. K. (1999). The cholinergic hypothesis of Alzheimer’s disease. Journal of Neurology, Neurosurgery & Psychiatry, 66(2), 137–147. [13] Goodsell, D. S., Morris, G. M., & Olson, A. J. (1996). Automated docking of flexible ligands: applications of AutoDock. Journal of molecular recognition, 9(1), 1-5. [14] Gujjeti, R. P., Namthabad, S., & Mamidala, E. (2014). HIV-1 reverse transcriptase inhibitory activity of Aerva lanata plant extracts. BMC Infectious Diseases, 14(Suppl 3), P12. [15] Gurrapu, S., & Mamidala, E. (2017). In Vitro HIV-1 reverse transcriptase inhibition of andrographolide isolated from Andrographis paniculata. European Journal of Biomedical, 4(12), 516-522. [16] Janakiramulu, P., & Mamidala, E. (2025). Molecular Docking and dynamic simulation analysis of flavonoid derivatives as COX-2 inhibitors. In Silico Pharmacology, 13(2), 59. [17] Janakiramulu, P., & Mamidala, E. (2025). Molecular Docking and dynamic simulation analysis of flavonoid derivatives as COX-2 inhibitors. In Silico Pharmacology, 13(2), 59. [18] Kitchen, D. B., Decornez, H., Furr, J. R., & Bajorath, J. (2004). Docking and scoring in virtual screening. Nature Reviews Drug Discovery, 3(11), 935–949. [19] Kryger, G., Silman, I., & Sussman, J. L. (1999). Structure of acetylcholinesterase complexed with E2020 (Aricept®): implications for the design of new anti-Alzheimer drugs. Structure, 7(3), 297-307. [20] Kumar Thatipamula, R., Narsimha, S., Battula, K., Chary, V. R., Mamidala, E., & Reddy, N. V. (2017). Synthesis, anticancer and antibacterial evaluation of novel (isopropylidene) uridine-[1, 2, 3] triazole hybrids. Journal of Saudi Chemical Society, 21(7), 795-802. [21] Kumar, M. P., Mamidala, E., Al-Ghanim, K., Al-Misned, F., Ahmed, Z., & Mahboob, S. (2020). Effects of D-Limonene on aldose reductase and protein glycation in diabetic rats. Journal of King Saud University-Science, 32(3), 1953-1958. [22] Lionta, E., Spyrou, G., Vassilatis, D. K., & Cournia, Z. (2014). Structure-based virtual screening for drug disc
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