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Mini-Reviews in Medicinal Chemistry


ISSN (Print): 1389-5575
ISSN (Online): 1875-5607

Review Article

Computational Studies on Acetylcholinesterase Inhibitors: From Biochemistry to Chemistry

Author(s): Kiran Bagri, Ashwani Kumar*, Manisha and Parvin Kumar

Volume 20 , Issue 14 , 2020

Page: [1403 - 1435] Pages: 33

DOI: 10.2174/1389557520666191224144346

Price: $65


Acetylcholinesterase inhibitors are the most promising therapeutics for Alzheimer’s disease treatment as these prevent the loss of acetylcholine and slows the progression of the disease. The drugs approved for the management of Alzheimer’s disease by the FDA are acetylcholinesterase inhibitors but are associated with side effects. Consistent and stringent efforts by the researchers with the help of computational methods opened new ways of developing novel molecules with good acetylcholinesterase inhibitory activity. In this manuscript, we reviewed the studies that identified the essential structural features of acetylcholinesterase inhibitors at the molecular level as well as the techniques like molecular docking, molecular dynamics, quantitative structure-activity relationship, virtual screening, and pharmacophore modelling that were used in designing these inhibitors.

Keywords: Acetylcholinesterase enzyme, Alzheimer's disease, Docking, QSAR, Virtual Screening, Pharmacophore, Molecular Dynamics.

Graphical Abstract
Suh, W.; Suslick, K.; Suh, Y. Therapeutic agents for alzheimer’s disease. Curr. Med. Chem. Cent. Nerv. Syst. Agents, 2005, 5(4), 259-269.
Prince, M.; Wimo, A.; Ali, G.C.; Guerchet, M.; Wu, Y.T.; Prina, M. The global impact of dementia. An analysis of prevalence, incidence, cost and trends. World Alzheimer Report 2015, 2015.
Du, X.; Wang, X.; Geng, M. Alzheimer’s disease hypothesis and related therapies. Transl. Neurodegener., 2018, 7, 2.
[] [PMID: 29423193]
Verma, S.; Kumar, A.; Tripathi, T.; Kumar, A. Muscarinic and nicotinic acetylcholine receptor agonists: Current scenario in Alzheimer’s disease therapy. J. Pharm. Pharmacol., 2018, 70(8), 985-993.
[] [PMID: 29663387]
Femminella, G.D.; Thayanandan, T.; Calsolaro, V.; Komici, K.; Rengo, G.; Corbi, G.; Ferrara, N. Imaging and molecular mechanisms of alzheimer’s disease: A review. Int. J. Mol. Sci., 2018, 19(12), 3702.
[] [PMID: 30469491]
Ferreira-Vieira, T.H.; Guimaraes, I.M.; Silva, F.R.; Ribeiro, F.M. Alzheimer’s disease: Targeting the cholinergic system. Curr. Neuropharmacol., 2016, 14(1), 101-115.
[] [PMID: 26813123]
Dale, H.H. The action of certain esters and ethers of choline, and their relation to muscarine. J. Pharmacol. Exp. Ther., 1914, 6(2), 147-190.
Contestabile, A. The history of the cholinergic hypothesis. Behav. Brain Res., 2011, 221(2), 334-340.
[] [PMID: 20060018]
Maurer, S.V.; Williams, C.L. The cholinergic system modulates memory and hippocampal plasticity via its interactions with non-neuronal cells. Front. Immunol., 2017, 8, 1489.
[] [PMID: 29167670]
Francis, P.T.; Palmer, A.M.; Snape, M.; Wilcock, G.K. The cholinergic hypothesis of Alzheimer’s disease: A review of progress. J. Neurol. Neurosurg. Psychiatry, 1999, 66(2), 137-147.
[] [PMID: 10071091]
Crismon, M.L. Tacrine: First drug approved for Alzheimer’s disease. Ann. Pharmacother., 1994, 28(6), 744-751.
[] [PMID: 7919566]
Qizilbash, N.; Birks, J.; López Arrieta, J.; Lewington, S.; Szeto, S. WITHDRAWN: Tacrine for Alzheimer’s disease. Cochrane Database Syst. Rev., 2007, 18(3)CD000202
[PMID: 17636619]
Pepeu, G.; Giovannini, M.G.; Bracco, L. Effect of cholinesterase inhibitors on attention. Chem. Biol. Interact., 2013, 203(1), 361-364.
[] [PMID: 23047023]
Pepeu, G.; Giovannini, M.G. Cholinesterase inhibitors and memory. Chem. Biol. Interact., 2010, 187(1-3), 403-408.
[] [PMID: 19941841]
Araujo, J.A.; Greig, N.H.; Ingram, D.K.; Sandin, J.; de Rivera, C.; Milgram, N.W. Cholinesterase inhibitors improve both memory and complex learning in aged beagle dogs. J. Alzheimers Dis., 2011, 26(1), 143-155.
[] [PMID: 21593569]
Anand, P.; Singh, B. A review on cholinesterase inhibitors for Alzheimer’s disease. Arch. Pharm. Res., 2013, 36(4), 375-399.
[] [PMID: 23435942]
Galimberti, D.; Scarpini, E. Old and new acetylcholinesterase inhibitors for Alzheimer’s disease. Expert Opin. Investig. Drugs, 2016, 25(10), 1181-1187.
[] [PMID: 27459153]
Patocka, J.; Kuca, K.; Jun, D. Acetylcholinesterase and butyrylcholinesterase--important enzymes of human body. Acta Med. (Hradec Kralove), 2004, 47(4), 215-228.
[] [PMID: 15841900]
Wiesner, J.; Kriz, Z.; Kuča, K.; Jun, D.; Koca, J. Acetylcholinesterases--the structural similarities and differences. J. Enzyme Inhib. Med. Chem., 2007, 22(4), 417-424.
[] [PMID: 17847707]
Singh, M.; Kaur, M.; Kukreja, H.; Chugh, R.; Silakari, O.; Singh, D. Acetylcholinesterase inhibitors as Alzheimer therapy: From nerve toxins to neuroprotection. Eur. J. Med. Chem., 2013, 70, 165-188.
[] [PMID: 24148993]
Colović, M.B.; Krstić, D.Z.; Lazarević-Pašti, T.D.; Bondžić, A.M.; Vasić, V.M. Acetylcholinesterase inhibitors: Pharmacology and toxicology. Curr. Neuropharmacol., 2013, 11(3), 315-335.
[] [PMID: 24179466]
Soreq, H.; Seidman, S. Acetylcholinesterase--new roles for an old actor. Nat. Rev. Neurosci., 2001, 2(4), 294-302.
[] [PMID: 11283752]
Dougherty, D.A.; Stauffer, D.A. Acetylcholine binding by a synthetic receptor: Implications for biological recognition. Science, 1990, 250(4987), 1558-1560.
[] [PMID: 2274786]
Sussman, J.L.; Silman, I. Determination by x-ray crystallography of the three dimensional- structure of acetylcholinesterase from torpedo electric organ, 65, Available from:.
Sussman, J.L.; Harel, M.; Frolow, F.; Oefner, C.; Goldman, A.; Toker, L.; Silman, I. Atomic structure of acetylcholinesterase from Torpedo californica: A prototypic acetylcholine-binding protein. Science, 1991, 253(5022), 872-879.
[] [PMID: 1678899]
Dvir, H.; Silman, I.; Harel, M.; Rosenberry, T.L.; Sussman, J.L. Acetylcholinesterase: From 3D structure to function. Chem. Biol. Interact., 2010, 187(1-3), 10-22.
[] [PMID: 20138030]
Doytchinova, I.; Atanasova, M.; Stavrakov, G.; Philipova, I.; Zheleva-Dimitrova, D. Galantamine derivatives as acetylcholinesterase inhibitors: Docking, design, synthesis, and inhibitory activity. In: Computational Modeling of Drugs Against Alzheimer’s Disease; Neuromethods; Roy, K., Ed.; Humana Press: New York. , 2017; 187, pp. (Vol. 132)163-176.
Cheung, J.; Gary, E.N.; Shiomi, K.; Rosenberry, T.L. Structures of human acetylcholinesterase bound to dihydrotanshinone I and territrem B show peripheral site flexibility. ACS Med. Chem. Lett., 2013, 4(11), 1091-1096.
[] [PMID: 24900610]
Kračmarová, A.; Drtinová, L.; Pohanka, M. Possibility of acetylcholinesterase overexpression in alzheimer’s disease patients after therapy with acetylcholinesterase inhibitors. Acta Med. (Hradec Kralove), 2015, 58(2), 37-42.
[] [PMID: 26455564]
Kacker, P.; Bottegoni, G.; Cavalli, A. Computational methods in the discovery and design of BACE-1 inhibitors. Curr. Med. Chem., 2012, 19(36), 6095-6111.
[] [PMID: 23072352]
Xu, Y.; Cheng, S.; Sussman, J.L.; Silman, I.; Jiang, H. Computational studies on acetylcholinesterases. Molecules, 2017, 22(8), 1486.
[] [PMID: 28796192]
Gilson, M.K.; Straatsma, T.P.; McCammon, J.A.; Ripoll, D.R.; Faerman, C.H.; Axelsen, P.H.; Silman, I.; Sussman, J.L. Open “back door” in a molecular dynamics simulation of acetylcholinesterase. Science, 1994, 263(5151), 1276-1278.
[] [PMID: 8122110]
Sanson, B.; Colletier, J.P.; Xu, Y.; Lang, P.T.; Jiang, H.; Silman, I.; Sussman, J.L.; Weik, M. Backdoor opening mechanism in acetylcholinesterase based on X-ray crystallography and molecular dynamics simulations. Protein Sci., 2011, 20(7), 1114-1118.
[] [PMID: 21594947]
Nachon, F.; Stojan, J.; Fournier, D. Insights into substrate and product traffic in the Drosophila melanogaster acetylcholinesterase active site gorge by enlarging a back channel. FEBS J., 2008, 275(10), 2659-2664.
[] [PMID: 18422651]
Tai, K.; Shen, T.; Henchman, R.H.; Bourne, Y.; Marchot, P.; McCammon, J.A. Mechanism of acetylcholinesterase inhibition by fasciculin: A 5-ns molecular dynamics simulation. J. Am. Chem. Soc., 2002, 124(21), 6153-6161.
[] [PMID: 12022850]
Bui, J.M.; Tai, K.; McCammon, J.A. Acetylcholinesterase: Enhanced fluctuations and alternative routes to the active site in the complex with fasciculin-2. J. Am. Chem. Soc., 2004, 126(23), 7198-7205.
[] [PMID: 15186156]
Wlodek, S.T.; Clark, T.W.; Scott, L.R.; McCammon, J.A. Molecular dynamics of acetylcholinesterase dimer complexed with tacrine. J. Am. Chem. Soc., 1997, 119(40), 9513-9522.
Zhou, H.X.; Wlodek, S.T.; McCammon, J.A. Conformation gating as a mechanism for enzyme specificity. Proc. Natl. Acad. Sci. USA, 1998, 95(16), 9280-9283.
[] [PMID: 9689071]
Bui, J.M.; Henchman, R.H.; McCammon, J.A. The dynamics of ligand barrier crossing inside the acetylcholinesterase gorge. Biophys. J., 2003, 85(4), 2267-2272.
[] [PMID: 14507691]
Cheng, S.; Song, W.; Yuan, X.; Xu, Y. Gorge motions of acetylcholinesterase revealed by microsecond molecular dynamics simulations. Sci. Rep., 2017, 7(1), 3219.
[] [PMID: 28607438]
Chandar, N.B.; Efremenko, I.; Silman, I.; Martin, J.M.L.; Sussman, J.L. Molecular dynamics simulations of the interaction of Mouse and Torpedo acetylcholinesterase with covalent inhibitors explain their differential reactivity: Implications for drug design. Chem. Biol. Interact., 2019, 310108715
[] [PMID: 31226285]
Tai, K.; Shen, T.; Börjesson, U.; Philippopoulos, M.; McCammon, J.A. Analysis of a 10-ns molecular dynamics simulation of mouse acetylcholinesterase. Biophys. J., 2001, 81(2), 715-724.
[] [PMID: 11463620]
Kryger, G.; Silman, I.; Sussman, J.L. Structure of acetylcholinesterase complexed with E2020 (Aricept): Implications for the design of new anti-Alzheimer drugs. Structure, 1999, 7(3), 297-307.
[] [PMID: 10368299]
Harel, M.; Schalk, I.; Ehret-Sabatier, L.; Bouet, F.; Goeldner, M.; Hirth, C.; Axelsen, P.H.; Silman, I.; Sussman, J.L. Quaternary ligand binding to aromatic residues in the active-site gorge of acetylcholinesterase. Proc. Natl. Acad. Sci. USA, 1993, 90(19), 9031-9035.
[] [PMID: 8415649]
Xu, Y.; Colletier, J.P.; Weik, M.; Jiang, H.; Moult, J.; Silman, I.; Sussman, J.L. Flexibility of aromatic residues in the active-site gorge of acetylcholinesterase: X-ray versus molecular dynamics. Biophys. J., 2008, 95(5), 2500-2511.
[] [PMID: 18502801]
Axelsen, P.H.; Harel, M.; Silman, I.; Sussman, J.L. Structure and dynamics of the active site gorge of acetylcholinesterase: Synergistic use of molecular dynamics simulation and X-ray crystallography. Protein Sci., 1994, 3(2), 188-197.
[] [PMID: 8003956]
Koellner, G.; Kryger, G.; Millard, C.B.; Silman, I.; Sussman, J.L.; Steiner, T. Active-site gorge and buried water molecules in crystal structures of acetylcholinesterase from Torpedo californica. J. Mol. Biol., 2000, 296(2), 713-735.
[] [PMID: 10669619]
Henchman, R.H.; Tai, K.; Shen, T.; McCammon, J.A. Properties of water molecules in the active site gorge of acetylcholinesterase from computer simulation. Biophys. J., 2002, 82(5), 2671-2682.
[] [PMID: 11964254]
Henchman, R.H.; McCammon, J.A. Structural and dynamic properties of water around acetylcholinesterase. Protein Sci., 2002, 11(9), 2080-2090.
[] [PMID: 12192064]
Shi, J.; Tai, K.; McCammon, J.A.; Taylor, P.; Johnson, D.A. Nanosecond dynamics of the mouse acetylcholinesterase cys69-cys96 omega loop. J. Biol. Chem., 2003, 278(33), 30905-30911.
[] [PMID: 12759360]
Boyd, A.E.; Dunlop, C.S.; Wong, L.; Radic, Z.; Taylor, P.; Johnson, D.A. Nanosecond dynamics of acetylcholinesterase near the active center gorge. J. Biol. Chem., 2004, 279(25), 26612-26618.
[] [PMID: 15078872]
Wiesner, J.; Kříž, Z.; Kuča, K.; Jun, D.; Koča, J. Influence of the acetylcholinesterase active site protonation on omega loop and active site dynamics. J. Biomol. Struct. Dyn., 2010, 28(3), 393-403.
[] [PMID: 20919754]
Tõugu, V. Acetylcholinesterase: Mechanism of catalysis and inhibition. Curr. Med. Chem., 2001, 1(2), 155-170.
[PMID: 11172672]
Groenhof, G. Introduction to QM/MM simulations. Methods Mol. Biol., 2013, 924, 43-66.
[] [PMID: 23034745]
Zhang, Y.; Kua, J.; McCammon, J.A. Role of the catalytic triad and oxyanion hole in acetylcholinesterase catalysis: An ab initio QM/MM study. J. Am. Chem. Soc., 2002, 124(35), 10572-10577.
[] [PMID: 12197759]
Zhou, Y.; Wang, S.; Zhang, Y. Catalytic reaction mechanism of acetylcholinesterase determined by Born-Oppenheimer ab initio QM/MM molecular dynamics simulations. J. Phys. Chem. B, 2010, 114(26), 8817-8825.
[] [PMID: 20550161]
Prada-Gracia, D.; Huerta-Yépez, S.; Moreno-Vargas, L.M. Application of computational methods for anticancer drug discovery, design, and optimization. Bol. Méd. Hosp. Infant. México, 2016, 73(6), 411-423.
[] [PMID: 29421286]
Ramírez, D. Computational methods applied to rational drug design. Open Med. Chem. J., 2016, 10, 7-20.
[] [PMID: 27708723]
Yu, W.; MacKerell, A.D., Jr Computer-aided drug design methods. Methods Mol. Biol., 2017, 1520, 85-106.
[] [PMID: 27873247]
Bermúdez-Lugo, J.A.; Rosales-Hernández, M.C.; Deeb, O.; Trujillo-Ferrara, J.; Correa-Basurto, J. In silico methods to assist drug developers in acetylcholinesterase inhibitor design. Curr. Med. Chem., 2011, 18(8), 1122-1136.
[] [PMID: 21291371]
Ferreira, L.G.; Dos Santos, R.N.; Oliva, G.; Andricopulo, A.D. Molecular docking and structure-based drug design strategies. Molecules, 2015, 20(7), 13384-13421.
[] [PMID: 26205061]
Pagadala, N.S.; Syed, K.; Tuszynski, J. Software for molecular docking: A review. Biophys. Rev., 2017, 9(2), 91-102.
[] [PMID: 28510083]
Korabecny, J.; Musilek, K.; Holas, O.; Binder, J.; Zemek, F.; Marek, J.; Pohanka, M.; Opletalova, V.; Dohnal, V.; Kuca, K. Synthesis and in vitro evaluation of N-alkyl-7-methoxytacrine hydrochlorides as potential cholinesterase inhibitors in Alzheimer disease. Bioorg. Med. Chem. Lett., 2010, 20(20), 6093-6095.
[] [PMID: 20817518]
Korabecny, J.; Musilek, K.; Holas, O.; Nepovimova, E.; Jun, D.; Zemek, F.; Opletalova, V.; Patocka, J.; Dohnal, V.; Nachon, F.; Hroudová, J.; Fisar, Z.; Kuca, K. Synthesis and in vitro evaluation of N-(Bromobut-3-en-2-yl)-7-methoxy-1,2,3,4-tetrahydroacridin-9-amine as a cholinesterase inhibitor with regard to Alzheimer’s disease treatment. Molecules, 2010, 15(12), 8804-8812.
[] [PMID: 21127466]
Korabecny, J.; Musilek, K.; Zemek, F.; Horova, A.; Holas, O.; Nepovimova, E.; Opletalova, V.; Hroudová, J.; Fisar, Z.; Jung, Y.S.; Kuca, K. Synthesis and in vitro evaluation of 7-methoxy-N-(pent-4-enyl)-1,2,3,4-tetrahydroacridin-9-amine-new tacrine derivate with cholinergic properties. Bioorg. Med. Chem. Lett., 2011, 21(21), 6563-6566.
[] [PMID: 21920739]
Korabecny, J.; Dolezal, R.; Cabelova, P.; Horova, A.; Hruba, E.; Ricny, J.; Sedlacek, L.; Nepovimova, E.; Spilovska, K.; Andrs, M.; Musilek, K.; Opletalova, V.; Sepsova, V.; Ripova, D.; Kuca, K. 7-MEOTA-donepezil like compounds as cholinesterase inhibitors: Synthesis, pharmacological evaluation, molecular modeling and QSAR studies. Eur. J. Med. Chem., 2014, 82, 426-438.
[] [PMID: 24929293]
Hamulakova, S.; Janovec, L.; Hrabinova, M.; Kristian, P.; Kuca, K.; Banasova, M.; Imrich, J. Synthesis, design and biological evaluation of novel highly potent tacrine congeners for the treatment of Alzheimer’s disease. Eur. J. Med. Chem., 2012, 55, 23-31.
[] [PMID: 22818849]
Samadi, A.; Valderas, C.; de los Ríos, C.; Bastida, A.; Chioua, M.; González-Lafuente, L.; Colmena, I.; Gandía, L.; Romero, A.; Del Barrio, L.; Martín-de-Saavedra, M.D.; López, M.G.; Villarroya, M.; Marco-Contelles, J. Cholinergic and neuroprotective drugs for the treatment of Alzheimer and neuronal vascular diseases. II. Synthesis, biological assessment, and molecular modelling of new tacrine analogues from highly substituted 2-aminopyridine-3-carbonitriles. Bioorg. Med. Chem., 2011, 19(1), 122-133.
[] [PMID: 21163662]
Spilovska, K.; Korabecny, J.; Kral, J.; Horova, A.; Musilek, K.; Soukup, O.; Drtinova, L.; Gazova, Z.; Siposova, K.; Kuca, K. 7-Methoxytacrine-adamantylamine heterodimers as cholinesterase inhibitors in Alzheimer’s disease treatment--synthesis, biological evaluation and molecular modeling studies. Molecules, 2013, 18(2), 2397-2418.
[] [PMID: 23429378]
Hamulakova, S.; Janovec, L.; Hrabinova, M.; Spilovska, K.; Korabecny, J.; Kristian, P.; Kuca, K.; Imrich, J. Synthesis and biological evaluation of novel tacrine derivatives and tacrine-coumarin hybrids as cholinesterase inhibitors. J. Med. Chem., 2014, 57(16), 7073-7084.
[] [PMID: 25089370]
Roy, K.K.; Tota, S.; Tripathi, T.; Chander, S.; Nath, C.; Saxena, A.K. Lead optimization studies towards the discovery of novel carbamates as potent AChE inhibitors for the potential treatment of Alzheimer’s disease. Bioorg. Med. Chem., 2012, 20(21), 6313-6320.
[] [PMID: 23026084]
Maalej, E.; Chabchoub, F.; Samadi, A.; de los Ríos, C.; Perona, A.; Morreale, A.; Marco-Contelles, J. Synthesis, biological assessment and molecular modeling of 14-aryl-10,11,12,14-tetrahydro-9H-benzo5,6chromeno2,3-bquinolin-13-amines. Bioorg. Med. Chem. Lett., 2011, 21(8), 2384-2388.
[] [PMID: 21411323]
Maalej, E.; Chabchoub, F.; Oset-Gasque, M.J.; Esquivias-Pérez, M.; González, M.P.; Monjas, L.; Pérez, C.; de los Ríos, C.; Rodríguez-Franco, M.I.; Iriepa, I.; Moraleda, I.; Chioua, M.; Romero, A.; Marco-Contelles, J.; Samadi, A. Synthesis, biological assessment, and molecular modeling of racemic 7-aryl-9,10,11,12-tetrahydro-7H-benzo7,8chromeno2,3-bquinolin-8-amines as potential drugs for the treatment of Alzheimer’s disease. Eur. J. Med. Chem., 2012, 54, 750-763.
[] [PMID: 22795665]
Khoobi, M.; Alipour, M.; Moradi, A.; Sakhteman, A.; Nadri, H.; Razavi, S.F.; Ghandi, M.; Foroumadi, A.; Shafiee, A. Design, synthesis, docking study and biological evaluation of some novel tetrahydrochromeno 3′,4′:5,6pyrano2,3-bquinolin-6(7H)-one derivatives against acetyl- and butyrylcholinesterase. Eur. J. Med. Chem., 2013, 68, 291-300.
[] [PMID: 23988412]
Adhami, H.R.; Linder, T.; Kaehlig, H.; Schuster, D.; Zehl, M.; Krenn, L. Catechol alkenyls from Semecarpus anacardium: Acetylcholinesterase inhibition and binding mode predictions. J. Ethnopharmacol., 2012, 139(1), 142-148.
[] [PMID: 22075454]
Khorana, N.; Changwichit, K.; Ingkaninan, K.; Utsintong, M. Prospective acetylcholinesterase inhibitory activity of indole and its analogs. Bioorg. Med. Chem. Lett., 2012, 22(8), 2885-2888.
[] [PMID: 22425563]
Islam, M.R.; Zaman, A.; Jahan, I.; Chakravorty, R.; Chakraborty, S. In silico QSAR analysis of quercetin reveals its potential as therapeutic drug for Alzheimer’s disease. J. Young Pharm., 2013, 5(4), 173-179.
[] [PMID: 24563598]
Naaz, H.; Singh, S.; Pandey, V.P.; Singh, P.; Dwivedi, U.N. Anti-cholinergic alkaloids as potential therapeutic agents for Alzheimer’s disease: An in silico approach. Indian J. Biochem. Biophys., 2013, 50(2), 120-125.
[PMID: 23720886]
Razavi, S.F.; Khoobi, M.; Nadri, H.; Sakhteman, A.; Moradi, A.; Emami, S.; Foroumadi, A.; Shafiee, A. Synthesis and evaluation of 4-substituted coumarins as novel acetylcholinesterase inhibitors. Eur. J. Med. Chem., 2013, 64, 252-259.
[] [PMID: 23644208]
Shi, D.H.; Huang, W.; Li, C.; Wang, L.T.; Wang, S.F. Synthesis, biological evaluation and molecular modeling of aloe-emodin derivatives as new acetylcholinesterase inhibitors. Bioorg. Med. Chem., 2013, 21(5), 1064-1073.
[] [PMID: 23380475]
Fang, J.; Wu, P.; Yang, R.; Gao, L.; Li, C.; Wang, D.; Wu, S.; Liu, A.L.; Du, G.H. Inhibition of acetylcholinesterase by two genistein derivatives: Kinetic analysis, molecular docking and molecular dynamics simulation. Acta Pharm. Sin. B, 2014, 4(6), 430-437.
[] [PMID: 26579414]
Genheden, S.; Ryde, U. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin. Drug Discov., 2015, 10(5), 449-461.
[] [PMID: 25835573]
Akrami, H.; Mirjalili, B.F.; Khoobi, M.; Nadri, H.; Moradi, A.; Sakhteman, A.; Emami, S.; Foroumadi, A.; Shafiee, A. Indolinone-based acetylcholinesterase inhibitors: Synthesis, biological activity and molecular modeling. Eur. J. Med. Chem., 2014, 84, 375-381.
[] [PMID: 25036795]
Somani, G.; Kulkarni, C.; Shinde, P.; Shelke, R.; Laddha, K.; Sathaye, S. In vitro acetylcholinesterase inhibition by psoralen using molecular docking and enzymatic studies. J. Pharm. Bioallied Sci., 2015, 7(1), 32-36.
[] [PMID: 25709334]
Rahim, F.; Javed, M.T.; Ullah, H.; Wadood, A.; Taha, M.; Ashraf, M. Qurat-ul-Ain; Khan, M.A.; Khan, F.; Mirza, S.; Khan, K.M. Synthesis, molecular docking, acetylcholinesterase and butyrylcholinesterase inhibitory potential of thiazole analogs as new inhibitors for Alzheimer disease. Bioorg. Chem., 2015, 62, 106-116.
[] [PMID: 26318401]
Piplani, P.; Danta, C.C. Design and synthesis of newer potential 4-(N-acetylamino)phenol derived piperazine derivatives as potential cognition enhancers. Bioorg. Chem., 2015, 60, 64-73.
[] [PMID: 25965977]
Kulshreshtha, A.; Piplani, P. Ameliorative effects of amide derivatives of 1,3,4-thiadiazoles on scopolamine induced cognitive dysfunction. Eur. J. Med. Chem., 2016, 122, 557-573.
[] [PMID: 27448914]
Gutiérrez, M.; Arévalo, B.; Martínez, G.; Valdés, F.; Vallejos, G.; Carmona, U.; San-Martín, A. Synthesis, molecular docking and design of tetrahydroquinolines as acetylcholinesterase inhibitors. J. Chem. Pharm. Res., 2015, 73, 351-358.
Ortiz, J.E.; Pigni, N.B.; Andujar, S.A.; Roitman, G.; Suvire, F.D.; Enriz, R.D.; Tapia, A.; Bastida, J.; Feresin, G.E. Alkaloids from hippeastrum argentinum and their cholinesterase-inhibitory activities: An in vitro and in silico study. J. Nat. Prod., 2016, 79(5), 1241-1248.
[] [PMID: 27096334]
Parlar, S.; Bayraktar, G.; Tarikogullari, A.H.; Alptüzün, V.; Erciyas, E. Synthesis, biological evaluation and molecular docking study of hydrazone-containing pyridinium salts as cholinesterase inhibitors. Chem. Pharm. Bull. (Tokyo), 2016, 64(9), 1281-1287.
[] [PMID: 27581632]
Chigurupati, S.; Selvaraj, M.; Mani, V.; Selvarajan, K.K.; Mohammad, J.I.; Kaveti, B.; Bera, H.; Palanimuthu, V.R.; Teh, L.K.; Salleh, M.Z. Identification of novel acetylcholinesterase inhibitors: Indolopyrazoline derivatives and molecular docking studies. Bioorg. Chem., 2016, 67, 9-17.
[] [PMID: 27231830]
Castillo-Ordóñez, W.O.; Tamarozzi, E.R.; da Silva, G.M.; Aristizabal-Pachón, A.F.; Sakamoto-Hojo, E.T.; Takahashi, C.S.; Giuliatti, S. Exploration of the acetylcholinesterase inhibitory activity of some alkaloids from amaryllidaceae family by molecular docking in silico. Neurochem. Res., 2017, 42(10), 2826-2830.
[] [PMID: 28497342]
Soyer, Z.; Uysal, S.; Parlar, S.; Tarikogullari Dogan, A.H.; Alptuzun, V. Synthesis and molecular docking studies of some 4-phthalimidobenzenesulfonamide derivatives as acetylcholinesterase and butyrylcholinesterase inhibitors. J. Enzyme Inhib. Med. Chem., 2017, 32(1), 13-19.
[] [PMID: 27766908]
Cristian Ferreira Neto, D.; de Souza Ferreira, M.; da Conceição Petronilho, E.; Lima, J.A. Oliveira Francisco de Azeredo, Sirlene de Oliveira Carneiro Brum, J.; Nascimento, C.; Daniel Figueroa Villar, J. A new guanylhydrazone derivative as a potential acetylcholinesterase inhibitor for Alzheimer’s disease: Synthesis, molecular docking, biological evaluation and kinetic studies by nuclear magnetic resonance. RSC Adv., 2017, 7, 33944-33952.
Sonmez, F.; Zengin Kurt, B.; Gazioglu, I.; Basile, L.; Dag, A.; Cappello, V.; Ginex, T.; Kucukislamoglu, M.; Guccione, S. Design, synthesis and docking study of novel coumarin ligands as potential selective acetylcholinesterase inhibitors. J. Enzyme Inhib. Med. Chem., 2017, 32(1), 285-297.
[] [PMID: 28097911]
Geromichalos, G.D.; Lamari, F.N.; Papandreou, M.A.; Trafalis, D.T.; Margarity, M.; Papageorgiou, A.; Sinakos, Z. Saffron as a source of novel acetylcholinesterase inhibitors: Molecular docking and in vitro enzymatic studies. J. Agric. Food Chem., 2012, 60(24), 6131-6138.
[] [PMID: 22655699]
Kiametis, A.S.; Silva, M.A.; Romeiro, L.A.; Martins, J.B.; Gargano, R. Potential acetylcholinesterase inhibitors: Molecular docking, molecular dynamics, and in silico prediction. J. Mol. Model., 2017, 23(2), 67.
[] [PMID: 28185116]
Shrivastava, S.K.; Srivastava, P.; Upendra, T.V.R.; Tripathi, P.N.; Sinha, S.K. Design, synthesis and evaluation of some N-methylenebenzenamine derivatives as selective acetylcholinesterase (AChE) inhibitor and antioxidant to enhance learning and memory. Bioorg. Med. Chem., 2017, 25(4), 1471-1480.
[] [PMID: 28126439]
Sharma, A.; Piplani, P. Design and synthesis of some acridine-piperazine hybrids for the improvement of cognitive dysfunction. Chem. Biol. Drug Des., 2017, 90(5), 926-935.
[] [PMID: 28544619]
Zhang, L.; Li, D.; Cao, F.; Xiao, W.; Zhao, L.; Ding, G.; Wang, Z.Z. Identification of human acetylcholinesterase inhibitors from the constituents of egb761 by modeling docking and molecular dynamics simulations. Comb. Chem. High Throughput Screen., 2018, 21(1), 41-49.
[] [PMID: 29173156]
Caliandro, R.; Pesaresi, A.; Cariati, L.; Procopio, A.; Oliverio, M.; Lamba, D. Kinetic and structural studies on the interactions of Torpedo californica acetylcholinesterase with two donepezil-like rigid analogues. J. Enzyme Inhib. Med. Chem., 2018, 33(1), 794-803.
[] [PMID: 29651884]
Chen, Y.; Bian, Y.; Sun, Y.; Kang, C.; Yu, S.; Fu, T.; Li, W.; Pei, Y.; Sun, H. Identification of 4-aminoquinoline core for the design of new cholinesterase inhibitors. Peer J, 2016, 4e, 2140.
[] [PMID: 27441112]
Piplani, P.; Jain, A.; Devi, D. Anjali; Sharma, A.; Silakari, P. Design, synthesis and pharmacological evaluation of some novel indanone derivatives as acetylcholinesterase inhibitors for the management of cognitive dysfunction. Bioorg. Med. Chem., 2018, 26(1), 215-224.
[] [PMID: 29195794]
Wu, G.; Gao, Y.; Kang, D.; Huang, B.; Huo, Z.; Liu, H.; Poongavanam, V.; Zhan, P.; Liu, X. Design, synthesis and biological evaluation of tacrine-1,2,3-triazole derivatives as potent cholinesterase inhibitors. MedChemComm, 2017, 9(1), 149-159.
[] [PMID: 30108908]
Basile, L. Virtual Screening in the Search of New and Potent Anti-Alzheimer agents. In: Computational Modelling of Drugs Against Alzheimer’s Disease; Humana Press: New York, 2017; Vol. 132, pp. 107-137.
Lavecchia, A.; Di Giovanni, C. Virtual screening strategies in drug discovery: A critical review. Curr. Med. Chem., 2013, 20(23), 2839-2860.
[] [PMID: 23651302]
Sopkova-de Oliveira Santos, J.; Lesnard, A.; Agondanou, J.H.; Dupont, N.; Godard, A.M.; Stiebing, S.; Rochais, C.; Fabis, F.; Dallemagne, P.; Bureau, R.; Rault, S. Virtual screening discovery of new acetylcholinesterase inhibitors issued from CERMN chemical library. J. Chem. Inf. Model., 2010, 50(3), 422-428.
[] [PMID: 20196555]
Chaudhaery, S.S.; Roy, K.K.; Shakya, N.; Saxena, G.; Sammi, S.R.; Nazir, A.; Nath, C.; Saxena, A.K. Novel carbamates as orally active acetylcholinesterase inhibitors found to improve scopolamine-induced cognition impairment: Pharmacophore-based virtual screening, synthesis, and pharmacology. J. Med. Chem., 2010, 53(17), 6490-6505.
[] [PMID: 20684567]
Berg, L.; Andersson, C.D.; Artursson, E.; Hörnberg, A.; Tunemalm, A.K.; Linusson, A.; Ekström, F. Targeting acetylcholinesterase: identification of chemical leads by high throughput screening, structure determination and molecular modeling. PLoS One, 2011, 6(11)e26039
[] [PMID: 22140425]
da Silva, V.B.; de Andrade, P.; Kawano, D.F.; Morais, P.A.; de Almeida, J.R.; Carvalho, I.; Taft, C.A.; da Silva, C.H. In silico design and search for acetylcholinesterase inhibitors in Alzheimer’s disease with a suitable pharmacokinetic profile and low toxicity. Future Med. Chem., 2011, 3(8), 947-960.
[] [PMID: 21707398]
Lu, S.H.; Wu, J.W.; Liu, H.L.; Zhao, J.H.; Liu, K.T.; Chuang, C.K.; Lin, H.Y.; Tsai, W.B.; Ho, Y. The discovery of potential acetylcholinesterase inhibitors: A combination of pharmacophore modeling, virtual screening, and molecular docking studies. J. Biomed. Sci., 2011, 18, 8.
[] [PMID: 21251245]
Chen, Y.; Fang, L.; Peng, S.; Liao, H.; Lehmann, J.; Zhang, Y. Discovery of a novel acetylcholinesterase inhibitor by structure-based virtual screening techniques. Bioorg. Med. Chem. Lett., 2012, 22(9), 3181-3187.
[] [PMID: 22472693]
Ambure, P.; Kar, S.; Roy, K. Pharmacophore mapping-based virtual screening followed by molecular docking studies in search of potential acetylcholinesterase inhibitors as anti-Alzheimer’s agents. Biosystems, 2014, 116, 10-20.
[] [PMID: 24325852]
Chitranshi, N.; Gupta, S.; Tripathi, P.K.; Seth, P.K. New molecular scaffolds for the design of alzheimer’s acetylcholinesterase inhibitors identified using ligand- and receptor-based virtual screening. Med. Chem. Res., 2013, 22(5), 2328-2345.
Nogara, P.A.; de Saraiva, R.A.; Caeran Bueno, D.; Lissner, L.J.; Lenz Della Corte, C.; Braga, M.M.; Rosemberg, D.B.; Rocha, J.B. Virtual screening of acetylcholinesterase inhibitors using the lipinski’s rule of five and zinc databank. BioMed Res. Int., 2014, 2015, 1-8.
Dhanjal, J.K.; Sharma, S.; Grover, A.; Das, A. Use of ligand-based pharmacophore modeling and docking approach to find novel acetylcholinesterase inhibitors for treating Alzheimer’s. Biomed. Pharmacother., 2015, 71, 146-152.
[] [PMID: 25960230]
Gupta, S.; Fallarero, A.; Järvinen, P.; Karlsson, D.; Johnson, M.S.; Vuorela, P.M.; Mohan, C.G. Discovery of dual binding site acetylcholinesterase inhibitors identified by pharmacophore modeling and sequential virtual screening techniques. Bioorg. Med. Chem. Lett., 2011, 21(4), 1105-1112.
[] [PMID: 21273074]
Gupta, S.; Mohan, C.G. Dual binding site and selective acetylcholinesterase inhibitors derived from integrated pharmacophore models and sequential virtual screening. BioMed Res. Int., 2014, 2014291214
[] [PMID: 25050335]
Malik, R.; Choudhary, B.S.; Srivastava, S.; Mehta, P.; Sharma, M. Identification of novel acetylcholinesterase inhibitors through e-pharmacophore-based virtual screening and molecular dynamics simulations. J. Biomol. Struct. Dyn., 2017, 35(15), 3268-3284.
[] [PMID: 27782777]
Venkatesan, R.; Prabhakaran, R.; Madar, I.H.; Karuppiah, S.P. Theoretical designing of acetylcholine esterase (ache) inhibitors. MOJ Biorg. Org. Chem., 2018, 2(1), 27-30.
Zhang, Y.; Zhang, S.; Xu, G.; Yan, H.; Pu, Y.; Zuo, Z. The discovery of new acetylcholinesterase inhibitors derived from pharmacophore modeling, virtual screening, docking simulation and bioassays. Mol. Biosyst., 2016, 12(12), 3734-3742.
[] [PMID: 27801451]
Yellamma, K.; Jyothi, P. In silico approach for validation of maltol derivatives as acetylcholinesterase inhibitors. Int. J. Pharm. Sci. Rev. Res., 2016, 42(1), 300-306.
Telpoukhovskaia, M.A.; Patrick, B.O.; Rodríguez-Rodríguez, C.; Orvig, C. In silico to in vitro screening of hydroxypyridinones as acetylcholinesterase inhibitors. Bioorg. Med. Chem. Lett., 2016, 26(6), 1624-1628.
[] [PMID: 26869193]
Doytchinova, I.; Atanasova, M.; Valkova, I.; Stavrakov, G.; Philipova, I.; Zhivkova, Z.; Zheleva-Dimitrova, D.; Konstantinov, S.; Dimitrov, I. Novel hits for acetylcholinesterase inhibition derived by docking-based screening on ZINC database. J. Enzyme Inhib. Med. Chem., 2018, 33(1), 768-776.
[] [PMID: 29651876]
Neves, B.J.; Braga, R.C.; Melo-Filho, C.C.; Moreira-Filho, J.T.; Muratov, E.N.; Andrade, C.H. Andrade, C.H. Qsar-based virtual screening: Advances and applications in drug discovery. Front. Pharmacol., 2018, 9, 1275.
[] [PMID: 30524275]
Abdel-Ilah, L.; Veljovic, E.; Gurbeta, L.; Badnjevic, A. Applications of qsar Study in Drug Design. Int. J. Eng. Res. Tech., 2017.Available from:.
Vracko, M. Mathematical (Structural) Descriptors in QSAR: Applications in Drug Design and Environmental Toxicology In: Advances in Mathematical Chemistry and Applications; Bentham Books , 2015; Vol. 1, pp. 222-250.
Danishuddin; Khan, A.U. Descriptors and their selection methods in QSAR analysis: Paradigm for drug design. Drug Discov. Today, 2016, 21(8), 1291-1302.
[] [PMID: 27326911]
Roy, K.; Kar, S.; Das, R. Validation of QSAR Models. In: Understanding the Basics of QSAR for Applications in Pharmaceutical Science and Risk Assessment; Academic Press, 2015; Vol. 1, pp. 231-289.
Araújo, J.Q.; de Brito, M.A.; Hoelz, L.V.; de Alencastro, R.B.; Castro, H.C.; Rodrigues, C.R.; Albuquerque, M.G. Receptor-dependent (RD) 3D-QSAR approach of a series of benzylpiperidine inhibitors of human acetylcholinesterase (HuAChE). Eur. J. Med. Chem., 2011, 46(1), 39-51.
[] [PMID: 21074294]
Lv, W.; Xue, Y. Prediction of acetylcholinesterase inhibitors and characterization of correlative molecular descriptors by machine learning methods. Eur. J. Med. Chem., 2010, 45(3), 1167-1172.
[] [PMID: 20053484]
Gupta, S.; Fallarero, A.; Vainio, M.J.; Saravanan, P. Santeri Puranen.; Jarvinen, P.; Johnson, M.S.; Vuorela, P.M.; Mohan C.G. Molecular docking guided comparative gfa, g/pls, svm and ann models of structurally diverse dual binding site acetylcholinesterase inhibitors. Mol. Inform., 2011, 30(8), 689-706.
[PMID: 27467261]
Yan, A.; Wang, K. Quantitative structure and bioactivity relationship study on human acetylcholinesterase inhibitors. Bioorg. Med. Chem. Lett., 2012, 22(9), 3336-3342.
[] [PMID: 22460031]
Bitencourt, M.; Freitas, M.P.; Rittner, R. The MIA-QSAR method for the prediction of bioactivities of possible acetylcholinesterase inhibitors. Arch. Pharm. (Weinheim), 2012, 345(9), 723-728.
[] [PMID: 22674790]
Deb, P.K.; Sharma, A.; Piplani, P.; Akkinepally, R.R. Molecular docking and receptor-specific 3D-QSAR studies of acetylcholinesterase inhibitors. Mol. Divers., 2012, 16(4), 803-823.
[] [PMID: 22996404]
Vitorović-Todorović, M.D.; Cvijetić, I.N.; Juranić, I.O.; Drakulić, B.J. The 3D-QSAR study of 110 diverse, dual binding, acetylcholinesterase inhibitors based on alignment independent descriptors (GRIND-2). The effects of conformation on predictive power and interpretability of the models. J. Mol. Graph. Model., 2012, 38, 194-210.
[] [PMID: 23073222]
Chen, N.; Liu, C.; Zhao, L.; Zhang, H. 3D-QSAR study of multi-target-directed AchE inhibitors based on autodocking. Med. Chem. Res., 2012, 21(2), 245-256.
Li, Y.P.; Weng, X.; Ning, F.X.; Ou, J.B.; Hou, J.Q.; Luo, H.B.; Li, D.; Huang, Z.S.; Huang, S.L.; Gu, L.Q. 3D-QSAR studies of azaoxoisoaporphine, oxoaporphine, and oxoisoaporphine derivatives as anti-AChE and anti-AD agents by the CoMFA method. J. Mol. Graph. Model., 2013, 41, 61-67.
[] [PMID: 23500628]
Abuhamdah, S.; Habash, M.; Taha, M.O. Elaborate ligand-based modeling coupled with QSAR analysis and in silico screening reveal new potent acetylcholinesterase inhibitors. J. Comput. Aided Mol. Des., 2013, 27(12), 1075-1092.
[] [PMID: 24338032]
Gharaghani, S.; Khayamian, T.; Ebrahimi, M. Molecular dynamics simulation study and molecular docking descriptors in structure-based QSAR on acetylcholinesterase (AChE) inhibitors. SAR QSAR Environ. Res., 2013, 24(9), 773-794.
[] [PMID: 23863115]
Kumar, V.; Chadha, N.; Tiwari, A.; Sehgal, N.; Mishra, A. Prospective atom-based 3d-qsar model prediction, pharmacophore generation, and molecular docking study of carbamate derivatives as dual inhibitors of ache and mao-b for Alzheimer’s disease. Med. Chem. Res., 2014, 23(3), 1114-1122.
Goyal, M.; Grover, S.; Dhanjal, J.K.; Goyal, S.; Tyagi, C.; Grover, A. Molecular modelling studies on flavonoid derivatives as dual site inhibitors of human acetyl cholinesterase using 3d-qsar, pharmacophore and high throughput screening approaches. Med. Chem. Res., 2014, 23(4), 2122-2132.
Vats, C.; Dhanjal, J.K.; Goyal, S.; Bharadvaja, N.; Grover, A. Computational design of novel flavonoid analogues as potential ache inhibitors: Analysis using group-based qsar, molecular docking and molecular dynamics simulations. Struct. Chem., 2014, 26(2), 467-476.
Correa-Basurto, J.; Bello, M.; Rosales-Hernández, M.C.; Hernández-Rodríguez, M.; Nicolás-Vázquez, I.; Rojo-Domínguez, A.; Trujillo-Ferrara, J.G.; Miranda, R.; Flores-Sandoval, C.A. QSAR, docking, dynamic simulation and quantum mechanics studies to explore the recognition properties of cholinesterase binding sites. Chem. Biol. Interact., 2014, 209, 1-13.
[] [PMID: 24321698]
Wong, K.Y.; Mercader, A.G.; Saavedra, L.M.; Honarparvar, B.; Romanelli, G.P.; Duchowicz, P.R. QSAR analysis on tacrine-related acetylcholinesterase inhibitors. J. Biomed. Sci., 2014, 21, 84.
[] [PMID: 25239202]
Andersson, C.D.; Hillgren, J.M.; Lindgren, C.; Qian, W.; Akfur, C.; Berg, L.; Ekström, F.; Linusson, A. Benefits of statistical molecular design, covariance analysis, and reference models in QSAR: A case study on acetylcholinesterase. J. Comput. Aided Mol. Des., 2015, 29(3), 199-215.
[] [PMID: 25351962]
Lee, S.; Barron, M.G. Development of 3D-qsar model for acetylcholinesterase inhibitors using a combination of fingerprint, molecular docking, and structure-based pharmacophore approaches. Toxicol. Sci., 2015, 148(1), 60-70.
[] [PMID: 26202430]
Lee, S.; Barron, M.G. A mechanism-based 3D-QSAR approach for classification and prediction of acetylcholinesterase inhibitory potency of organophosphate and carbamate analogs. J. Comput. Aided Mol. Des., 2016, 30(4), 347-363.
[] [PMID: 27055524]
Pulikkal, B.P.; Marunnan, S.M.; Bandaru, S.; Yadav, M.; Nayarisseri, A.; Sureshkumar, S. Common sar derived from linear and non-linear qsar studies on ache inhibitors used in the treatment of alzheimer’s disease. Curr. Neuropharmacol., 2017, 15(8), 1093-1099.
[] [PMID: 27964704]
Gurung, A.B.; Aguan, K.; Mitra, S.; Bhattacharjee, A. Identification of molecular descriptors for design of novel Isoalloxazine derivatives as potential Acetylcholinesterase inhibitors against Alzheimer’s disease. J. Biomol. Struct. Dyn., 2017, 35(8), 1729-1742.
[] [PMID: 27410776]
Zhou, A.; Hu, J.; Wang, L.; Zhong, G.; Pan, J.; Wu, Z.; Hui, A. Combined 3D-QSAR, molecular docking, and molecular dynamics study of tacrine derivatives as potential acetylcholinesterase (AChE) inhibitors of Alzheimer’s disease. J. Mol. Model., 2015, 21(10), 277.
[] [PMID: 26438408]
Simeon, S.; Anuwongcharoen, N.; Shoombuatong, W.; Malik, A.A.; Prachayasittikul, V.; Wikberg, J.E.S.; Nantasenamat, C. Probing the origins of human acetylcholinesterase inhibition via QSAR modeling and molecular docking. Peer J., 2016., 4e2322.
[] [PMID: 7602288]
Veselinović, J.B.; Nikolić, G.M.; Trutić, N.V.; Živković, J.V.; Veselinović, A.M. Monte Carlo QSAR models for predicting organophosphate inhibition of acetycholinesterase. SAR QSAR Environ. Res., 2015, 26(6), 449-460.
[] [PMID: 26043064]
OECD; Guidance Document on the Validation of (Quantitative) Structure-Activity Relationship (Q)SAR Models In: OECD Series on Testing and Assessment; OECD Publishing: Paris. , 2014. (No.69)
Niu, B.; Zhao, M.; Su, Q.; Zhang, M. Lv, W.; Chen, Q.; Chen, F.; Chu, D.; Du, D.; Zhang, Y. 2D-sar and 3d-qsar analyses for acetylcholinesterase inhibitors. Mol. Divers., 2017, 21(2), 413-426.
[] [PMID: 28275924]
Zhang, S.; Hou, B.; Yang, H.; Zuo, Z. Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives. Arch. Pharm. Res., 2016, 39(5), 591-602.
[] [PMID: 26832327]
Bitam, S.; Hamadache, M.; Hanini, S. QSAR model for prediction of the therapeutic potency of N-benzylpiperidine derivatives as AChE inhibitors. SAR QSAR Environ. Res., 2017, 28(6), 471-489.
[] [PMID: 28610432]
Srivastava, P.; Tripathi, P.N.; Sharma, P.; Rai, S.N.; Singh, S.P.; Srivastava, R.K.; Shankar, S.; Shrivastava, S.K. Design and development of some phenyl benzoxazole derivatives as a potent acetylcholinesterase inhibitor with antioxidant property to enhance learning and memory. Eur. J. Med. Chem., 2019, 163, 116-135.
[] [PMID: 30503937]
De-la-Torre, P.; Treuer, A.V.; Gutiérrez, M.; Poblete, H.; Alzate-Morales, J.H.; Trilleras, J.; Astudillo-Saavedra, L.; Caballero, J. Synthesis and in silico analysis of the quantitative structure–activity relationship of heteroaryl–acrylonitriles as AChE inhibitor. J. Taiwan Inst. Chemic E., 2016, 59, 45-60.
Hossain, T.; Saha, A.; Mukherjee, A. Exploring molecular structural requirement for AChE inhibition through multi-chemometric and dynamics simulation analyses. J. Biomol. Struct. Dyn., 2018, 36(5), 1274-1285.
[] [PMID: 28417668]
Velázquez Libera, J.L.; Caballero, J.; Toropova, A.; Toropov, A. Estimation of 2d autocorrelation descriptors and 2d monte carlo descriptors as a tool to build up predictive models for acetylcholinesterase (ache) inhibitory activity. Chemom. Intell. Lab. Syst., 2018, 184, 14-21.

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