Login Register Cart 0
Generic placeholder image

Current Computer-Aided Drug Design

Editor-in-Chief

ISSN (Print): 1573-4099
ISSN (Online): 1875-6697

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Proposition of Potential GSK-3β Inhibitors for the Treatment of Alzheimer’s Disease: A Molecular Modeling Study

Author(s): Leandro L. Castro, Leide C. S. Picanço, Jaderson V. Silva, Lucilene R. Souza, Kessia P. A. Sousa, Abraão A. Pinheiro, Gisele A. Chaves, Hueldem R. C. Teixeira, Guilherme M. Silva, Carlton A. Taft, Carlos H.T. de P. da Silva and Lorane I. da S. Hage-Melim*

Volume 16, Issue 5, 2020

Page: [541 - 554] Pages: 14

DOI: 10.2174/1573409915666191015110734

Price: $65

Abstract

Introduction: The enzyme Glycogen Synthase Kinase 3-β (GSK-3β) is related to neuronal cell degeneration, representing a promising target to treat Alzheimer’s Disease (AD).

Methods: In this work, we performed a molecular modeling study of existing GSK-3β inhibitors by means of evaluation of their IC50 values, derivation of a pharmacophore model, molecular docking simulations, ADME/Tox properties predictions, molecular modifications and prediction of synthetic viability.

Results: In this manner, inhibitor 15 (CID 57399952) was elected a template molecule, since it demonstrated to bear relevant structural groups able to interact with GSK-3β, and also presented favorable ADME/Tox predicted properties, except for mutagenicity. Based on this inhibitor chemical structure we proposed six analogues that presented the absence of alerts for mutagenic and carcinogenic activity, both for rats and mouse; likewise they all presented low risk alerts for inhibition of hERG and medium prediction of synthetic viability.

Conclusion: It is concluded that the analogues of GSK-3β inhibitors were optimized in relation to the toxicity endpoint of the template molecule, being, therefore, presented as novel and promising drug candidates for AD treatment.

Keywords: Alzheimer’s disease, GSK-3β, molecular modeling, docking, toxicity, computer aided drug design.

« Previous Next »
Graphical Abstract

[1]
Selkoe, D.J. Alzheimer’s disease: genes, proteins, and therapy. Physiol. Rev., 2001, 81(2), 741-766.
[http://dx.doi.org/10.1152/physrev.2001.81.2.741] [PMID: 11274343]
[2]
Vinters, H.V. Emerging concepts in Alzheimer’s disease. Annu. Rev. Pathol., 2015, 10, 291-319.
[http://dx.doi.org/10.1146/annurev-pathol-020712-163927] [PMID: 25387055]
[3]
Hoblyn, J.; Mohanty, S.; Trinh, N.H.; Yaffe, K. Efficacy of cholinesterase inhibitors in the treatment of neuropsychiatric symptoms and functional impairment in Alzheimer disease: a meta-analysis. JAMA, 2003, 289, 210-216.
[http://dx.doi.org/10.1001/jama.289.2.210] [PMID: 12517232]
[4]
Clegg, A.; Green, C.; Kirby, J.; Loveman, E.; Payne, E.; Picot, J.; Takeda, A. The clinical and cost-effectiveness of donepezil, rivastigmine, galantamine and memantine for Alzheimer’s disease. Health Technol. Assess., 2006, 10(1), 1-160.
[5]
Bottino, C.M.; Carvalho, I.A.; Alvarez, A.M.M.A.; Avila, R.; Zukauskas, P.R.; Bustamante, S.E.; Andrade, F.C.; Hototian, S.R.; Saffi, F.; Camargo, C.H. Cognitive rehabilitation in Alzheimer’s disease patients: multidisciplinary team report. Arq. Neuropsiquiatr., 2002, 60(1), 70-79.
[http://dx.doi.org/10.1590/S0004-282X2002000100013] [PMID: 11965412]
[6]
Cazarin, K.C.C.; Corrêa, C.L.; Zambrone, F.A.D. Revista brasileira de ciências farmacêuticas. Revista Brasileira de Ciências Farmacêuticas, 2004, 40(3), 289-299.
[http://dx.doi.org/10.1590/S1516-93322004000300004]
[7]
Liu, T.; Lin, Y.; Wen, X.; Jorissen, R.N.; Gilson, M.K. BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities. Nucleic Acids Res., 2007, 35(1), D198-D201.
[8]
Li, Z.; Wan, H.; Shi, Y.; Ouyang, P. Quinic acid as a potent drug candidate for prostate cancer –- a comparative pharmacokinetic approach. J. Chem. Inf. Model., 2004, 44(5), 1886-1890.
[9]
Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev., 1997, 23, 3-25.
[http://dx.doi.org/10.1016/S0169-409X(96)00423-1]
[10]
Chemplus: Modular Extensions for HyperChem Release 6.02, Molecular Modeling for Windows.HyperClub, Inc.: Gainesville, 2000.
[11]
Freire, R.O.; Rocha, G.B.; Simas, A.M.; Stewart, J.J.P. RM1: a reparameterization of AM1 for H, C, N, O, P, S, F, Cl, Br, and I. J. Comput. Chem., 2006, 27, 1101-1111.
[http://dx.doi.org/10.1002/jcc.20425] [PMID: 16691568]
[12]
Coffman, V.C.; Wu, P.; Parthun, M.R.; Wu, J.Q. CENP-A exceeds microtubule attachment sites in centromere clusters of both budding and fission yeast. J. Cell Biol., 2011, 195(4), 563-572.
[http://dx.doi.org/10.1083/jcb.201106078] [PMID: 22084306]
[13]
Schneidman-Duhovny, D.; Dror, O.; Inbar, Y.; Nussinov, R.; Wolfson, H.J. PharmaGist: a webserver for ligand-based pharmacophore detection. Nucleic Acids Res., 2008, 36(Web Server issue), W223-8.
[http://dx.doi.org/10.1093/nar/gkn187] [PMID: 18424800]
[14]
Goodsell, D.S.; Olson, A.J. Automated docking of substrates to proteins by simulated annealing. Proteins, 1990, 8(3), 195-202.
[http://dx.doi.org/10.1002/prot.340080302] [PMID: 2281083]
[15]
Dietrich, S.W. Burger’s medicinal chemistry and drug discovery: principles and practice, 5th ed; John Wiley: New York, 1995.
[16]
Kwang, L.S. 2005.
[17]
Yamashita, S.; Furubayashi, T.; Kataoka, M.; Sakane, T.; Sezaki, H.; Tokuda, H. Optimized conditions for prediction of intestinal drug permeability using Caco-2 cells. Eur. J. Pharm. Sci., 2000, 10(3), 195-204.
[18]
Ridings, J.E.; Barratt, M.D.; Cary, R.; Earnshaw, C.G.; Eggington, C.E.; Ellis, M.K.; Judson, P.N.; Langowski, J.J.; Marchant, C.A.; Payne, M.P.; Watson, W.P.; Yih, T.D. Computer prediction of possible toxic action from chemical structure: an update on the DEREK system. Toxicology, 1996, 106(1-3), 267-279.
[http://dx.doi.org/10.1016/0300-483X(95)03190-Q] [PMID: 8571398]
[19]
Mohan, C.G.; Gandhi, T.; Garg, D.; Shinde, R. Computer-assisted methods in chemical toxicity prediction. Mini Rev. Med. Chem., 2007, 7(5), 499-507.
[http://dx.doi.org/10.2174/138955707780619554] [PMID: 17504185]
[20]
Cariello, N.F.; Wilson, J.D.; Britt, B.H.; Wedd, D.J.; Burlinson, B.; Gombar, V. Comparison of the computer programs DEREK and TOPKAT to predict bacterial mutagenicity. deductive estimate of risk from existing knowledge. Toxicity prediction by computer assisted technology. Mutagenesis, 2002, 17(4), 321-329.
[http://dx.doi.org/10.1093/mutage/17.4.321] [PMID: 12110629]
[21]
Poroikov, V.; Filimonov, D. Why relevant chemical information cannot be exchanged without disclosing structures? J. Computer-Aided Mol. Des., 2005, 19, 705-713.
[22]
Yuan, Y.; Pei, J.; Lai, L. LigBuilder 2: a practical de novo drug design approach. J. Chem. Inf. Model., 2011, 51(5), 1083-1091.
[http://dx.doi.org/10.1021/ci100350u] [PMID: 21513346]
[23]
Lenz, G.R.; Pajouhesh, H. Medicinal chemical properties of successful central nervous system drugs. NeuroRx, 2005, 2, 541-553.
[24]
Rankovic, Z. CNS drug design: balancing physicochemical properties for optimal brain exposure. J. Med. Chem., 2015, 58(6), 2584-2608.
[http://dx.doi.org/10.1021/jm501535r] [PMID: 25494650]
[25]
Picanço, L.C.S.; Castro, L.L.; Pinheiro, A.A.; Silva, R.K.; Souza, L.R.; Braga, F.S.; Silva, C.H.T.P.; Santos, C.B.R.; Hage-Melim, L.I.S. Study of molecular docking, physicochemical and pharmacokinetic properties of gsk-3β inhibitors. Br. J. Pharm. Res., 2015, 7(3), 152-175.
[http://dx.doi.org/10.9734/BJPR/2015/18054]
[26]
Fang, M.; Wang, J.; Zhang, X.; Geng, Y.; Hu, Z.; Rudd, J.A.; Ling, S.; Chen, W.; Han, S. The miR-124 regulates the expression of BACE1/β-secretase correlated with cell death in Alzheimer’s disease. Toxicol. Lett., 2012, 209(1), 94-105.
[http://dx.doi.org/10.1016/j.toxlet.2011.11.032] [PMID: 22178568]
[27]
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.
[http://dx.doi.org/10.1016/j.biosystems.2013.12.002] [PMID: 24325852]
[28]
Coffman, K.; Brodney, M.; Cook, J.; Lanyon, L.; Pandit, J.; Sakya, S.; Schachter, J.; Tseng-Lovering, E.; Wessel, M. 6-amino-4-(pyrimidin-4-yl)pyridones: novel glycogen synthase kinase-3β inhibitors. Bioorg. Med. Chem. Lett., 2011, 21(5), 1429-1433.
[http://dx.doi.org/10.1016/j.bmcl.2011.01.017] [PMID: 21295469]
[29]
Kramer, T.; Monte, L. F. Schmidt, Small-Molecule inhibitors of gsk-3: structural insights and their application to alzheimer's disease models. B. Int. J. Alzheimer's Dis., 2012,, 2012.
[30]
Agrawal, R.; Bahare, R.S.; Dikshit, S.N.; Ganguly, S.; Jain, P. Ligand-based pharmacophore detection, screening of potential pharmacophore and docking studies, to get effective glycogen synthase kinase inhibitors. Med. Chem. Res., 2013, 22, 5504-5535.
[http://dx.doi.org/10.1007/s00044-013-0547-y]
[31]
Bag, S.; Ghosh, S.; Tulsan, R.; Sood, A.; Zhou, W.; Schifone, C.; Foster, M.; LeVine, H., III; Török, B.; Török, M. Design, synthesis and biological activity of multifunctional α,β-unsaturated carbonyl scaffolds for Alzheimer’s disease. Bioorg. Med. Chem. Lett., 2013, 23(9), 2614-2618.
[http://dx.doi.org/10.1016/j.bmcl.2013.02.103] [PMID: 23540646]
[32]
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., 2015, 26(2), 467-476.
[http://dx.doi.org/10.1007/s11224-014-0494-3]
[33]
Goyal, M.; Singh, S.; Sibinga, E.M.; Gould, N.F.; Rowland-Seymour, A.; Sharma, R.; Berger, Z.; Sleicher, D.; Maron, D.D.; Shihab, H.M.; Ranasinghe, P.D.; Linn, S.; Saha, S.; Bass, E.B.; Haythornthwaite, J.A. Meditation programs for psychological stress and well-being: a systematic review and meta-analysis. JAMA Intern. Med., 2014, 174(3), 357-368.
[http://dx.doi.org/10.1001/jamainternmed.2013.13018] [PMID: 24395196]
[34]
Cole, J.C.; Murray, C.W.; Nissink, J.W.M.; Taylor, R.D.; Taylor, R. Comparing protein–ligand docking programs is difficult. Proteins: Struc. Func Bioinf., 2005, 2005(60), 325-332.
[http://dx.doi.org/10.1002/prot.20497]
[35]
Ali, B. Ms Jamal, Q.; Shams, S.; Al-Wabel, A. In Silico analysis of green tea polyphenols as inhibitors of ache and bche enzymes in alzheimer’s disease treatment. CNS & Neurological DisordersDrug Targets (Formerly Current Drug Targets-CNS & Neurological Disorders), , 2016; 15, pp. (5)624-628.
[36]
Zeng, H.WU. X. Alzheimer’s disease drug development based on Computer-Aided Drug Design. Eur. J. Med. Chem., 2016, 121, 851-863.
[http://dx.doi.org/10.1016/j.ejmech.2015.08.039] [PMID: 26415837]
[37]
Razzaghi-Asl, N.; Aggarwal, N.; Srivastava, S.; Parmar, V.S.; Prasad, A.K.; Miri, R.; Firuzi, O. Inhibition of Alzheimer’s BACE-1 by 2,6-dialkyl-4-chromon-3-yl-1,4-dihydropyridine-3,5-dicarboxylates. Med. Chem. Res., 2015, 24(8), 3230-3241.
[http://dx.doi.org/10.1007/s00044-015-1367-z]
[38]
Seniya, C.; Khan, G. J.; Uchadia, K. Identification of potential herbal inhibitor of acetylcholinesterase associated Alzheimer's disorders using molecular docking and molecular dynamics simulation. Biochem. Res. Int., 2014, , 2014.
[39]
Meng, W.; Deshmukh, H.A.; van Zuydam, N.R.; Liu, Y.; Donnelly, L.A.; Zhou, K.; Morris, A.D.; Colhoun, H.M.; Palmer, C.N.; Smith, B.H. A genome-wide association study suggests an association of Chr8p21.3 (GFRA2) with diabetic neuropathic pain. Eur. J. Pain, 2015, 19(3), 392-399.
[http://dx.doi.org/10.1002/ejp.560] [PMID: 24974787]
[40]
Armstrong, A.W.; Armstrong, E.J.; Golan, D.E.; Tashjian, A.H.J. Princípios de farmacologia: A base fisiopatológica da farmacoterapia 2nd ed; Guanabara Koogan: Rio de Janeiro, 2009.
[41]
Klopman, G.; Stefan, L.R.; Saiakhov, R.D. ADME evaluation. 2. A computer model for the prediction of intestinal absorption in humans. Eur. J. Pharm. Sci., 2002, 17(4-5), 253-263.
[http://dx.doi.org/10.1016/S0928-0987(02)00219-1] [PMID: 12453615]
[42]
Li, A.P. Screening for human ADME/Tox drug properties in drug discovery. Drug Discov. Today, 2001, 6(7), 357-366.
[http://dx.doi.org/10.1016/S1359-6446(01)01712-3] [PMID: 11267922]
[43]
Glynn, S.L.; Hawi, A.; Wright, J.L. Yazdanian, Correlating Partitioning and Caco-2 cell permeability of structurally diverse small molecular weight compounds. M. Pharm. Res., 1998, 15, 1490-1494.
[44]
Ungell, A-L.B. Caco-2 replace or refine? Drug Discov. Today. Technol., 2004, 1(4), 423-430.
[PMID: 24981623]
[45]
Cheong, J.; Grove, J.R.; Irvine, J.D.; Lockhart, K.; Selick, H.E.; Takahashi, L.; Tolan, J.W. J. Pharm. Sci., 1999, 88, 28-33.
[http://dx.doi.org/10.1021/js9803205] [PMID: 9874698]
[46]
Brunton, L.; Hilal-Dandan, R. Goodman and Gilman’s: Manual of Pharmacology and Therapaeutics, 2nd ed; McGraw-Hill Ediction: New York, 2008.
[47]
Deane, R.; Bell, R.D.; Sagare, A.; Zlokovic, B.V. Antimalarial Drug Artemisinin Extenuates Amyloidogenesis and Neuroinflammation in APPswe/PS1dE9 Transgenic Mice via Inhibition of Nuclear Factor-jB and NLRP3 Inflammasome Activation. CNS & Neurological Disorders-Drug Targets (Formerly Current Drug Targets-CNS & Neurological Disorders), 2009, 8(1), 16-30.
[48]
Chen, C.; Ma, X.; Yang, J. Predictive model of blood-brain barrier penetration of organic compounds. Acta Pharmacol. Sin., 2005, 26, 500-512.
[http://dx.doi.org/10.1111/j.1745-7254.2005.00068.x] [PMID: 15780201]
[49]
Helma, C. Curr Opin Drug Discov Devel; Freiburg, 2004, 8, pp. (1)27-31.
[50]
Daston, G.P.; Rusyn, I. computational toxicology: realizing the promise of the toxicity testing in the 21st Century. Environ. Health Perspect., 2010, 118(8), 1047-1050.
[http://dx.doi.org/10.1289/ehp.1001925] [PMID: 20483702]
[51]
Hofnung, M.; Quillardet, P. The screening, diagnosis and evaluation of genotoxic agents with batteries of bacterial tests. Mutation Research, Amsterdam, 1988, 205, 107-118.
[http://dx.doi.org/10.1016/0165-1218(88)90014-6]
[52]
Ames, B.N.; Mccann, J.; Yamasaki, E. Methods for detecting carcinogens and mutagens with the Salmonella/mammalian-microsome mutagenicity test. Mutat. Res., 1975, 31(6), 347-364.
[http://dx.doi.org/10.1016/0165-1161(75)90046-1] [PMID: 768755]
[53]
Ames, B.N.; Maron, D.M. Revised methods for the Salmonella mutagenicity test. Mutat. Res., 1983, 113, 173-21.
[http://dx.doi.org/10.1016/0165-1161(83)90010-9] [PMID: 6341825]
[54]
Woo, Y.T. Patty’s Industrial Hygiene and Toxicology, 3rd ed; John Wiley: New York, 1981.
[55]
Cunha, E.L.; Santos, C.F.; Braga, F.S.; Costa, J.S.; Silva, R.C.; Favacho, H.A.; Santos, C.B. Computational investigation of antifungal compounds using molecular modeling and prediction of adme/tox properties. J. Comput. Theor. Nanosci., 2015, 12(10), 3682-3691.
[http://dx.doi.org/10.1166/jctn.2015.4260]
[56]
Camanho, L.E.M.; Ferreira, F.A.C.; Mendonça Filho, P.J.S.; Prata, I.; Saad, E.B.; Veronese, F.O. Preditores eletrocardiográficos de síncope e de morte súbita em portadores de síndrome do QT longo congênito/Electrocardiographic predictors of syncope and sudden death in patients with congenital long QT syndrome. Rev. SOCERJ., 2007, 20, 91-96.
[57]
Edward, W.; Kothiwale, S. Computational methods in drug discovery. Pharm. Rev., 2014, 66(1), 334-395.
[58]
Crawley, L. Evidence-based medicine. A new approach to teaching the practice of medicine. JAMA, 1992, 268, 2420-2425.
[http://dx.doi.org/10.1001/jama.1992.03490170092032] [PMID: 1404801]
[59]
Tocher, J.H. General Pharmacology. Vascular System, 1997, 28(4), 485-487.
[http://dx.doi.org/10.1016/S0306-3623(96)00283-2] [PMID: 9147012]
[60]
Hernandes, M.Z.; Cavalcanti, S.M.T.; Moreira, D.R.M.; de Azevedo, W.F., Junior; Leite, A.C.; Leite, A.C.L. Halogen atoms in the modern medicinal chemistry: hints for the drug design. Curr. Drug Targets, 2010, 11(3), 303-314.
[http://dx.doi.org/10.2174/138945010790711996] [PMID: 20210755]
[61]
Gabay, M.; Cabrera, M.; Maio, R.D.; Paez, J.A.; Campillo, N.; Lavaggi, M.L.; Cerecetto, H.; González, M. Mutagenicity of N-oxide containing heterocycles and related compounds: experimental and theoretical studies. Curr. Top. Med. Chem., 2014, 14(11), 1374-1387.
[http://dx.doi.org/10.2174/1568026614666140506123235] [PMID: 24805062]
[62]
Wickliffe, J.; Overton, E.; Frickel, S.; Howard, J.; Wilson, M.; Simon, B.; Miller, C. Environmental Health Perspectives (Online), 2014, 122(1), 6.
[http://dx.doi.org/10.1289/ehp.1306724]
[63]
Lopez, A.; Carmen, M.D. Introducción a la química farmacéutica, 2nd ed; , 2001.
[64]
Blass, B.E.; Abou-Gharbia, M.A.; Childers, W.E.; Ramanjulu, M.M.; Morton, G.C.U.S.U.S. Patent Application n. 14/595,344, 13 jan. 2015.
[65]
Chung, M.C.; Güido, R.V.C.; Martinelli, T.F.; Gonçalves, M.F.; Polli, M.C.; Botelho, K.C.A.; Varanda, E.A.; Colli, W.; Miranda, M.T.; Ferreira, E.I. Synthesis and in vitro evaluation of potential antichagasic hydroxymethylnitrofurazone (NFOH-121): a new nitrofurazone prodrug. Bioorg. Med. Chem., 2003, 11(22), 4779-4783.
[http://dx.doi.org/10.1016/j.bmc.2003.07.004] [PMID: 14556793]
[66]
Fier, P.S.; Hartwig, J.F. Selective C-H fluorination of pyridines and diazines inspired by a classic amination reaction. Science, 2013, 342(6161), 956-960.
[http://dx.doi.org/10.1126/science.1243759] [PMID: 24264986]
[67]
McKinney, J.D.; Richard, A.; Waller, C.; Newman, M.C.; Gerberick, F. The practice of structure activity relationships (SAR) in toxicology. Toxicol. Sci., 2000, 56(1), 8-17.
[http://dx.doi.org/10.1093/toxsci/56.1.8] [PMID: 10869449]
[68]
Prakash, G.K.; Zhang, Z.; Wang, F.; Munoz, S.; Olah, G.A. Nucleophilic trifluoromethylation of carbonyl compounds: trifluoroacetaldehyde hydrate as a trifluoromethyl source. J. Org. Chem., 2013, 78(7), 3300-3305.
[http://dx.doi.org/10.1021/jo400202w] [PMID: 23425346]
[69]
Gonsalves, A.A.; Araújo, C.R.M.; Leite Filho, C.A.; De Medeiros, F.S. Contextualizing acid-base reactions according to Brönsted-Lowry protonic theory using propranolol and nimesulide tablets. Quim. Nova, 2013, 36(8), 1236-1241.
[http://dx.doi.org/10.1590/S0100-40422013000800024]
[70]
Landelle, G.; Panossian, A.; Leroux, F.R. Trifluoromethyl ethers and -thioethers as tools for medicinal chemistry and drug discovery. Curr. Top. Med. Chem., 2014, 14(7), 941-951.
[http://dx.doi.org/10.2174/1568026614666140202210016] [PMID: 24484423]
[71]
Boda, K.; Seidel, T.; Gasteiger, J. Structure and reaction based evaluation of synthetic accessibility. J. Comput. Aided Mol. Des., 2007, 21(6), 311-325.
[http://dx.doi.org/10.1007/s10822-006-9099-2] [PMID: 17294248]

Rights & Permissions Print Cite
Article Metrics
20
© 2024 Bentham Science Publishers | Privacy Policy