Inhibition of Human Acetylcholinesterase (4EY7) using Bioactive Compound from Moringa oleifera: Molecular Docking and Dynamic Studies
Abstract
Alzheimer's disease is a neurodegenerative disorder caused by acetylcholine hydrolysis that impairs cognitive brain function. This research aims to determine the interaction and dynamic of ligands from Moringa oleifera on AChE through Lipinski's Rule, ADMET properties, molecular docking calculations, and molecular dynamic simulations. Lipinski's Rule calculation provided ligand limits that adhere to druglikeness properties. ADMET results also showed that several ligands satisfy ADMET properties. Pterygospermine has lower binding energy than the ligand control (-10.28 kcal mol-1) with amino acid residues of TYR133 and GLU202. It indicates a favorable interaction between the AChE receptor and ligand in the inhibition process. Based on molecular docking calculations, pterygospermine inhibits the AChE receptor at the Long, narrow aromatic gorge active site. According to molecular dynamic simulations, the MMPBSA energy for pterygospermine is 37.377 kJ mol-1. The samples showed a total average RMSD of 2 Å, suggesting no significant conformational changes throughout the simulation. The sample's average RMSF value is around 2 Å, suggesting favorable interactions with the receptor during simulation. However, this data is different from the ligand control interaction mode. Molecular dynamic investigations of the pterygospermine ligand in the complex revealed the stability and unfolded effect on the protein. The results of this study propose a candidate anti-Alzheimer's ligand from Moringa oleifera against the AChE receptor. In practice, these results can contribute to research studies exploring natural ingredients from plants with medicinal potential in drug discovery. These results can be validated using further research in vitro and in vivo.
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References
Karran E, De Strooper B. The Amyloid Hypothesis in Alzheimer Disease: New Insights from New Therapeutics. Nat Rev Drug Discov. 2022;21(4):306-318. doi:10.1038/s41573-022-00391-w
Pitchai A, Rajaretinam RK, Mani R, Nagarajan N. Molecular Interaction of Human Acetylcholinesterase with Trans-Tephrostachin and Derivatives for Alzheimer’s Disease. Heliyon. 2020;6(9):e04930. doi:10.1016/j.heliyon.2020.e04930
Lima E, Medeiros J. Marine Organisms as Alkaloid Biosynthesizers of Potential Anti-Alzheimer Agents. Mar Drugs. 2022;20(1):1-26. doi:10.3390/md20010075
Kuzu B, Tan M, Taslimi P, et al. Mono- or Di-Substituted Imidazole Derivatives for Inhibition of Aetylcholine and Butyrylcholine Esterases. Bioorg Chem. 2019;86(October 2018):187-196. doi:10.1016/j.bioorg.2019.01.044
Wang L, Moraleda I, Iriepa I, et al. 5-Methyl-: N -(8-(5,6,7,8-tetrahydroacridin-9-ylamino)octyl)-5 H -indolo[2,3- b] quinolin-11-amine: A Highly Potent Human Cholinesterase Inhibitor. Medchemcomm. 2017;8(6):1307-1317. doi:10.1039/c7md00143f
Malik YA, Awad TA, Abdalla M, et al. Chalcone Scaffolds Exhibiting Acetylcholinesterase Enzyme Inhibition: Mechanistic and Computational Investigations. Molecules. 2022;27(10):1-17. doi:10.3390/molecules27103181
Tallini LR, Manfredini G, Rodríguez-Escobar ML, et al. The Anti-Cholinesterase Potential of Fifteen Different Species of Narcissus L . (Amaryllidaceae) Collected in Spain. Life. 2024;14(536):1-15. doi.org/10.3390/life1404053
Farihi A, Bouhrim M, Chigr F, et al. Exploring Medicinal Herbs’ Therapeutic Potential and Molecular Docking Analysis for Compounds as Potential Inhibitors of Human Acetylcholinesterase in Alzheimer’s Disease Treatment. Med. 2023;59(10). doi:10.3390/medicina59101812
Ghimire S, Subedi L, Acharya N, et al. Moringa oleifera: A Tree of Life as a Promising Medicinal Plant for Neurodegenerative Diseases. J Agric Food Chem. 2021;69(48):14358-14371. doi:10.1021/acs.jafc.1c04581
Balkrishna A, Misra LN. Ayurvedic Plants in Brain Disorders: The Herbal Hope. J Tradit Med Clin Naturop. 2017;06(02):1-9. doi:10.4172/2573-4555.1000221
Djiogue S, Kammogne IY, Etet PS, et al. Neuroprotective Effects of the Aqueous Extract of Leaves of Moringa oleifera Neuroprotective Effects of the Aqueous Extract of Leaves of Moringa oleifera (Moringaceae) in Scopolamine-Treated Rats. 2022;(June). doi:10.35248/0974-8369.22.14.474
Magaji UF, Sacan O, Yanardag R. Antilipase, Antiacetylcholinesterase and Antioxidant Activities of Moringa oleifera Extracts. Rom All rights Reserv Rom Biotechnol Lett. 2022;27(1):3208-3214. doi:10.25083/rbl/27.1/3208-3214
Azlan UK, Annuar NAK, Mediani A, et al. An Insight Into The Neuroprotective and Anti-neuroinflammatory Effects and Mechanisms of Moringa oleifera. Front Pharmacol. 2023;13(January):1-18. doi:10.3389/fphar.2022.1035220
Kou X, Li B, Olayanju JB, et al. Nutraceutical or Pharmacological Potential of Moringa oleifera Lam. Nutrients. 2018;10(3). doi:10.3390/nu10030343
Amat-Ur-rasool H, Ahmed M, Hasnain S, et al. In Silico Design of Dual-Binding Site Anti-Cholinesterase Phytochemical Heterodimers as Treatment Options for Alzheimer’s Disease. Curr Issues Mol Biol. 2022;44(1):152-175. doi:10.3390/cimb44010012
Rocchetti G, Pagnossa JP, Blasi F, et al. Phenolic Profiling and In Vitro Bioactivity of Moringa oleifera Leaves as Affected by Different Extraction Solvents. Food Res Int. 2020;127. doi:10.1016/j.foodres.2019.108712
Mahaman YAR, Huang F, Wu M, et al. Moringa Oleifera Alleviates Homocysteine-Induced Alzheimer’s Disease-Like Pathology and Cognitive Impairments. J Alzheimer’s Dis. 2018;63(3):1141-1159. doi:10.3233/JAD-180091
Ludwig L, Seifert R. The decline in the clinical relevance of pilocarpine and physostigmine monitored in pharmacology textbooks from 1878 to 2023 : nine take ‑ home messages for future ( pharmacology ) textbook authors. Naunyn Schmiedebergs Arch Pharmacol. 2024;(0123456789):1-23. doi:10.1007/s00210-024-03558-x
Manogna C, Margesan T. In Silico and Pharmacokinetic Studies of Glucomoringin from Moringa oleifera Root for Alzheimer’s Disease Like Pathology. 2024;(September 2021). doi:10.2144/fsoa-2023-0255
Idoga ES, Ambali SF, Ayo JO, et al. Assessment of Antioxidant and Neuroprotective Activities of Methanol Extract of Moringa oleifera Lam. leaves in Subchronic Chlorpyrifos-Intoxicated Rats. Comp Clin Path. 2018;27(4):917-925. doi:10.1007/s00580-018-2682-9
Zhou J, Yang WS, Suo DQ, et al. Moringa oleifera Seed Extract Alleviates Scopolamine-Induced Learning and Memory Impairment in Mice. Front Pharmacol. 2018;9(APR):1-11. doi:10.3389/fphar.2018.00389
Ajala A, Eltayb WA, Abatyough TM, et al. In-silico Screening and ADMET evaluation of Therapeutic MAO-B Inhibitors against Parkinson Disease. Intell Pharm. 2023;(November 2023). doi:10.1016/j.ipha.2023.12.008
Kiruthiga N, Alagumuthu M, Selvinthanuja C, et al. Molecular Modelling, Synthesis and Evaluation of Flavone and Flavanone Scaffolds as Anti-inflammatory Agents. Antiinflamm Antiallergy Agents Med Chem. 2020;20(1):20-38. doi:10.2174/1871523019666200102112017
Mirza FJ, Zahid S, Amber S, et al. Multitargeted Molecular Docking and Dynamic Simulation Studies of Bioactive Compounds from Rosmarinus officinalis against Alzheimer’s Disease. Molecules. 2022;27(21):1-18. doi:10.3390/molecules27217241
Lipinski CA. Lead- and drug-like compounds: The Rule-Of-Five Revolution. Drug Discov Today Technol. 2004;1(4):337-341. doi:10.1016/j.ddtec.2004.11.007
Nainwal LM, Shaququzzaman M, Akhter M, et al. Synthesis, ADMET Prediction and Reverse Screening Study of 3,4,5-trimethoxy Phenyl Ring Pendant Sulfur‐Containing Cyanopyrimidine Derivatives As Promising Apoptosis Inducing Anticancer Agents. Bioorg Chem. 2020;104:104282. doi:10.1016/j.bioorg.2020.104282
Lipinski CA, Lombardo F, Dominy BW, et al. Experimental and Computational Approaches to Estimate Solubility and Permeability in Drug Discovery and Development Settings. Adv Drug Deliv Rev. 2012;64(SUPPL.):4-17. doi:10.1016/j.addr.2012.09.019
Pettersen EF, Goddard TD, Huang CC, et al. UCSF Chimera - A visualization System for Exploratory Research and Analysis. J Comput Chem. 2004;25(13):1605-1612. doi:10.1002/jcc.20084
Moss DE. Improving anti-neurodegenerative benefits of acetylcholinesterase inhibitors in alzheimer’s disease: Are irreversible inhibitors the future? Int J Mol Sci. 2020;21(10):1-18. doi:10.3390/ijms21103438
Morris GM, Goodsell DS, Halliday RS, et al. Automated Docking using a Lamarckian Genetic Algorithm and An Empirical Binding Free Energy Function. J Comput Chem. 1998;19(14):1639-1662. doi:10.1002/(SICI)1096-987X(19981115)19:14<1639::AID-JCC10>3.0.CO;2-B
Gaarett M. Morris, Goodsell DS, Halliday RS, et al. AutoDock4 and AutoDock Tools4: Automated Docking with Selective Receptor Flexibility. J Comput Chem. 2012;32:174-182. doi:10.1002/jcc
Humble HL and MS. YASARA: A Tool to Obtain Structural Guidance in Biocatalytic Investigations. Protein Eng. 2017;1685:43-67.
Shakil S. Molecular Interaction of Inhibitors with Human Brain Butyrylcholinesterase. EXCLI J. 2021;20:1597-1607. doi:10.17179/excli2021-4418
Yamamoto E, Akimoto T, Mitsutake A, et al. Universal Relation between Instantaneous Diffusivity and Radius of Gyration of Proteins in Aqueous Solution. Phys Rev Lett. 2021;126(12):1-20. doi:10.1103/PhysRevLett.126.128101
Shin HK, Kang Y, No KT. 2016. Predicting ADME Properties of Chemicals. In Handbook of Computational Chemistry. Springer Science Business Media Dordrecht.
Daina A, Zoete V.A BOILED-Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules. ChemMedChem. Published online 2016:1117-1121. doi:10.1002/cmdc.201600182
Zhai J, Man VH, Ji B, Cai L, Wang J. Comparison and summary of in silico prediction tools for CYP450-mediated drug metabolism. Drug Discov Today. 2023;28(10):103728. doi:10.1016/j.drudis.2023.103728
Mardianingrum R, Susilawati D, Ruswanto R. Computational Study of 1-(3-Nitrobenzoyloxymethyl)-5-Fluorouracil Derivatives as Colorectal Cancer Agents. J Kim Val. 2022;8(2):211-220. doi:10.15408/jkv.v8i2.25489
Allgaier M, Allgaier C. An update on Drug Treatment Options of Alzheimer’s disease. Frontiers Biosci. 2014;19:1345-1354.
Rezaul Islam M, Akash S, Murshedul Islam M, et al. Alkaloids as drug leads in Alzheimer’s treatment: Mechanistic and therapeutic insights. Brain Res. 2024;1834(February):148886. doi:10.1016/j.brainres.2024.148886
Jamal QMS, Khan MI, Alharbi AH, et al. Identification of Natural Compounds of the Apple as Inhibitors against Cholinesterase for the Treatment of Alzheimer’s Disease: An In Silico Molecular Docking Simulation and ADMET Study. Nutrients. 2023;15(7). doi:10.3390/nu15071579
Peitzika SC, Pontiki E. A Review on Recent Approaches on Molecular Docking Studies of Novel Compounds Targeting Acetylcholinesterase in Alzheimer Disease. Molecules. 2023;28(3):1-28. doi:10.3390/molecules28031084
Huey R, Morris GM, Olson AJ, et al. A Semiempirical Free Energy Force Field with Charge‐Based Desolvation. J Comput Chem. 2006;28(6):1145-1152.
Bouamrane S, Khaldan A, Alaqarbeh M, et al. Garlic as an effective antifungal inhibitor : A combination of reverse docking , molecular dynamics simulation , ADMET screening , DFT , and retrosynthesis studies. 2024;17(July 2023). https://doi.org/10.1016/j.arabjc.2024.105642
Maharani DA, Adelina R, Aini AQ, et al. Molecular Docking and Dynamic Simulation of Erythrina fusca Lour Chemical Compounds Targeting VEGFR-2 Receptor for Anti-Liver Cancer Activity. Published online 2024. doi:10.15408/jkv.v10i1.3
Irsal RAP, Gholam GM, Dwicesaria MA, et al. Computational Investigation of Y. aloifolia variegate as anti-Human Immunodeficiency Virus (HIV) Targeting HIV-1 Protease: A Multiscale In-Silico Exploration. Pharmacol Res - Mod Chinese Med. 2024;11(June):100451. doi:10.1016/j.prmcm.2024.100451
Mitra S, Dash R. Structural Dynamics and Quantum Mechanical Aspects of Shikonin Derivatives as CREBBP Bromodomain Inhibitors. J Mol Graph Model. 2018;83:42-52. doi:10.1016/j.jmgm.2018.04.014
Das B, Moumita S, Ghosh S, et al. Biosynthesis of Magnesium Oxide (MgO) Nanoflakes by using Leaf Extract of Bauhinia purpurea and Evaluation of Its Antibacterial Property Against Staphylococcus aureus. Mater Sci Eng C. 2018;91(May):436-444. doi:10.1016/j.msec.2018.05.059
Aldeghi M, Bodkin MJ, Knapp S, et al. Statistical Analysis on the Performance of Molecular Mechanics Poisson-Boltzmann Surface Area versus Absolute Binding Free Energy Calculations: Bromodomains as a Case Study. J Chem Inf Model. 2017;57(9):2203-2221. doi:10.1021/acs.jcim.7b00347
Trott A, Olson AJ. Software News and Updates Gabedit — A Graphical User Interface for Computational Chemistry Softwares. J Comput Chem. 2012;32:174-182. doi:10.1002/jc
DOI: 10.15408/jkv.v10i2.39840
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