Generic placeholder image

Current Neuropharmacology


ISSN (Print): 1570-159X
ISSN (Online): 1875-6190

Review Article

Potential Therapeutic Approaches to Alzheimer’s Disease By Bioinformatics, Cheminformatics And Predicted Adme-Tox Tools

Author(s): Speranta Avram, Maria Mernea*, Carmen Limban, Florin Borcan and Carmen Chifiriuc

Volume 18, Issue 8, 2020

Page: [696 - 719] Pages: 24

DOI: 10.2174/1570159X18666191230120053

Price: $65


Background: Alzheimer’s disease (AD) is considered a severe, irreversible and progressive neurodegenerative disorder. Currently, the pharmacological management of AD is based on a few clinically approved acethylcholinesterase (AChE) and N-methyl-D-aspartate (NMDA) receptor ligands, with unclear molecular mechanisms and severe side effects.

Methods: Here, we reviewed the most recent bioinformatics, cheminformatics (SAR, drug design, molecular docking, friendly databases, ADME-Tox) and experimental data on relevant structurebiological activity relationships and molecular mechanisms of some natural and synthetic compounds with possible anti-AD effects (inhibitors of AChE, NMDA receptors, beta-secretase, amyloid beta (Aβ), redox metals) or acting on multiple AD targets at once. We considered: (i) in silico supported by experimental studies regarding the pharmacological potential of natural compounds as resveratrol, natural alkaloids, flavonoids isolated from various plants and donepezil, galantamine, rivastagmine and memantine derivatives, (ii) the most important pharmacokinetic descriptors of natural compounds in comparison with donepezil, memantine and galantamine.

Results: In silico and experimental methods applied to synthetic compounds led to the identification of new AChE inhibitors, NMDA antagonists, multipotent hybrids targeting different AD processes and metal-organic compounds acting as Aβ inhibitors. Natural compounds appear as multipotent agents, acting on several AD pathways: cholinesterases, NMDA receptors, secretases or Aβ, but their efficiency in vivo and their correct dosage should be determined.

Conclusion: Bioinformatics, cheminformatics and ADME-Tox methods can be very helpful in the quest for an effective anti-AD treatment, allowing the identification of novel drugs, enhancing the druggability of molecular targets and providing a deeper understanding of AD pathological mechanisms.

Keywords: Alzheimer`s disease, bioinformatics, cheminformatics, synthetic and natural compounds, QSAR, docking.

Graphical Abstract
Dos Santos Picanço, L.C.; Ozela, P.F.; de Fátima de Brito Brito, M.; Pinheiro, A.A.; Padilha, E.C.; Braga, F.S.; de Paula da Silva, C.H.; Dos Santos, C.B.; Rosa, J.M.; da Silva Hage-Melim, L.I. Alzheimer’s disease: A review from the pathophysiology to diagnosis, new perspectives for pharmacological treatment. Curr. Med. Chem., 2018, 25(26), 3141-3159.
[PMID: 27978805]
Prince, M.; Wimo, A.; Guerchet, M. World Alzheimer report 2015: the global impact of dementia; Alzheimer’s Disease International, 2015.
Bano, S.; Rasheed, M.A.; Jamil, F.; Ibrahim, M.; Kanwal, S. In silico identification of novel Apolipoprotein E4 inhibitor for Alzheimer’s disease therapy., 2018, 15(1), 97-103.
Veitch, D.P.; Weiner, M.W.; Aisen, P.S.; Beckett, L.A.; Cairns, N.J.; Green, R.C.; Harvey, D.; Jack, C.R., Jr; Jagust, W.; Morris, J.C.; Petersen, R.C.; Saykin, A.J.; Shaw, L.M.; Toga, A.W.; Trojanowski, J.Q. Understanding disease progression and improving Alzheimer’s disease clinical trials: recent highlights from the alzheimer’s disease neuroimaging initiative. Alzheimers Dement., 2018, 15(1), 106-152.
[PMID: 30321505]
Alladi, S.; Hachinski, V. World dementia: One approach does not fit all. Neurology, 2018, 91(6), 264-270.
[] [PMID: 29997191]
Dourlen, P.; Chapuis, J.; Lambert, J-C. Using high-throughput animal or cell-based models to functionally characterize GWAS signals. Curr. Genet. Med. Rep., 2018, 6(3), 107-115.
[] [PMID: 30147999]
Zheng, J.J.; Li, W.X.; Liu, J.Q.; Guo, Y.C.; Wang, Q.; Li, G.H.; Dai, S.X.; Huang, J.F. Low expression of aging-related NRXN3 is associated with Alzheimer disease: A systematic review and meta-analysis. Medicine (Baltimore), 2018, 97(28), e11343.
[] [PMID: 29995770]
Desikan, R.S.; Fan, C.C.; Wang, Y.; Schork, A.J.; Cabral, H.J.; Cupples, L.A.; Thompson, W.K.; Besser, L.; Kukull, W.A.; Holland, D.; Chen, C.H.; Brewer, J.B.; Karow, D.S.; Kauppi, K.; Witoelar, A.; Karch, C.M.; Bonham, L.W.; Yokoyama, J.S.; Rosen, H.J.; Miller, B.L.; Dillon, W.P.; Wilson, D.M.; Hess, C.P.; Pericak-Vance, M.; Haines, J.L.; Farrer, L.A.; Mayeux, R.; Hardy, J.; Goate, A.M.; Hyman, B.T.; Schellenberg, G.D.; McEvoy, L.K.; Andreassen, O.A.; Dale, A.M. Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score. PLoS Med., 2017, 14(3), e1002258.
[] [PMID: 28323831]
Levy, B.R.; Slade, M.D.; Pietrzak, R.H.; Ferrucci, L. Positive age beliefs protect against dementia even among elders with high-risk gene. PLoS One, 2018, 13(2), e0191004.
[] [PMID: 29414991]
Falsetti, L.; Viticchi, G.; Buratti, L.; Grigioni, F.; Capucci, A.; Silvestrini, M. Interactions between atrial fibrillation, cardiovascular risk factors, and apoe genotype in promoting cognitive decline in patients with Alzheimer’s Disease: A Prospective Cohort Study. J. Alzheimers Dis., 2018, 62(2), 713-725.
[] [PMID: 29480173]
Femminella, G.D.; Taylor-Davies, G.; Scott, J.; Edison, P. Do cardiometabolic risk factors influence amyloid, tau, and neuronal function in apoe4 carriers and non-carriers in alzheimer’s disease trajectory? J. Alzheimers Dis., 2018, 64(3), 981-993.
[] [PMID: 29966204]
Kivipelto, M.; Mangialasche, F.; Ngandu, T. Lifestyle interventions to prevent cognitive impairment, dementia and Alzheimer disease. Nat. Rev. Neurol., 2018, 14(11), 653-666.
[] [PMID: 30291317]
Alford, S.; Patel, D.; Perakakis, N.; Mantzoros, C.S. Obesity as a risk factor for Alzheimer’s disease: weighing the evidence. Obes. Rev., 2018, 19(2), 269-280.
[] [PMID: 29024348]
Lardenoije, R.; Iatrou, A.; Kenis, G.; Kompotis, K.; Steinbusch, H.W.; Mastroeni, D.; Coleman, P.; Lemere, C.A.; Hof, P.R.; van den Hove, D.L.; Rutten, B.P. The epigenetics of aging and neurodegeneration. Prog. Neurobiol., 2015, 131, 21-64.
[] [PMID: 26072273]
Pena-Bautista, C.; Baquero, M.; Vento, M.; Chafer-Pericas, C. Omics-based biomarkers for the early Alzheimer Disease diagnosis and reliable therapeutic targets development. Curr. Neuropharmacol., 2019, 17(7), 630-647.
[PMID: 30255758]
Lardenoije, R.; Pishva, E.; Lunnon, K.; van den Hove, D.L. Neuroepigenetics of aging and age-related neurodegenerative disorders. Prog. Mol. Biol. Transl. Sci., 2018, 158, 49-82.
[] [PMID: 30072060]
Stoccoro, A.; Coppedè, F. Role of epigenetics in Alzheimer’s disease pathogenesis. Neurodegener. Dis. Manag., 2018, 8(3), 181-193.
[] [PMID: 29888987]
Ramos de Matos, M.; Ferreira, C.; Herukka, S.K.; Soininen, H.; Janeiro, A.; Santana, I.; Baldeiras, I.; Almeida, M.R.; Lleó, A.; Dols-Icardo, O.; Alcolea, D.; Benussi, L.; Binetti, G.; Paterlini, A.; Ghidoni, R.; Nacmias, B.; Meulenbroek, O.; van Waalwijk van Doorn, L.J.C.; Kuiperi, H.B.J.; Hausner, L.; Waldemar, G.; Simonsen, A.H.; Tsolaki, M.; Gkatzima, O.; Resende de Oliveira, C.; Verbeek, M.M.; Clarimon, J.; Hiltunen, M.; de Mendonça, A.; Martins, M. Quantitative genetics validates previous genetic variants and identifies novel genetic players influencing alzheimer’s disease cerebrospinal fluid biomarkers. J. Alzheimers Dis., 2018, 66(2), 639-652.
[] [PMID: 30320580]
Yoshino, Y.; Yamazaki, K.; Ozaki, Y.; Sao, T.; Yoshida, T.; Mori, T.; Mori, Y.; Ochi, S.; Iga, J.I.; Ueno, S.I. INPP5D mRNA expression and cognitive decline in Japanese Alzheimer’s Disease subjects. J. Alzheimers Dis., 2017, 58(3), 687-694.
[] [PMID: 28482637]
Stage, E.; Duran, T.; Risacher, S.L.; Goukasian, N.; Do, T.M.; West, J.D.; Wilhalme, H.; Nho, K.; Phillips, M.; Elashoff, D.; Saykin, A.J.; Apostolova, L.G. The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism. Alzheimers Dement. (Amst.), 2016, 5, 53-66.
[] [PMID: 28054028]
López-Riquelme, N.; Alom-Poveda, J.; Viciano-Morote, N.; Llinares-Ibor, I.; Tormo-Díaz, C.; Apolipoprotein, E. Apolipoprotein E ε4 allele and malondialdehyde level are independent risk factors for Alzheimer’s disease. SAGE Open Med., 2016, 42050312115626731.
[] [PMID: 26835020]
Berkowitz, C.L.; Mosconi, L.; Rahman, A.; Scheyer, O.; Hristov, H.; Isaacson, R.S. Clinical application of apoe in alzheimer’s prevention: a precision medicine approach. J. Prev. Alzheimers Dis., 2018, 5(4), 245-252.
[PMID: 30298183]
Sanabria-Castro, A.; Alvarado-Echeverría, I.; Monge-Bonilla, C. Molecular pathogenesis of Alzheimer’s Disease: An Update. Ann. Neurosci., 2017, 24(1), 46-54.
[] [PMID: 28588356]
Shen, Y.; Ye, B.; Chen, P.; Wang, Q.; Fan, C.; Shu, Y.; Xiang, M. Cognitive decline, dementia, Alzheimer’s Disease and Presbycusis: Examination of the Possible Molecular Mechanism. Front. Neurosci., 2018, 12, 394.
[] [PMID: 29937713]
Davies, P.; Maloney, A.J. Selective loss of central cholinergic neurons in Alzheimer’s disease. Lancet, 1976, 2(8000), 1403.
[] [PMID: 63862]
Bartus, R.T.; Dean, R.L., III; Beer, B.; Lippa, A.S. The cholinergic hypothesis of geriatric memory dysfunction. Science, 1982, 217(4558), 408-414.
[] [PMID: 7046051]
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]
Douchamps, V.; Mathis, C. A second wind for the cholinergic system in Alzheimer's therapy. Behav Pharmacol, 2017, 28(2 and 3-Spec Issue), 112-123.
Bohnen, N.I.; Grothe, M.J.; Ray, N.J.; Müller, M.L.T.M.; Teipel, S.J. Recent advances in cholinergic imaging and cognitive decline-Revisiting the cholinergic hypothesis of dementia. Curr. Geriatr. Rep., 2018, 7(1), 1-11.
[] [PMID: 29503795]
Hasselmo, M.E. The role of acetylcholine in learning and memory. Curr. Opin. Neurobiol., 2006, 16(6), 710-715.
[] [PMID: 17011181]
McHardy, S.F.; Wang, H.L.; McCowen, S.V.; Valdez, M.C. Recent advances in acetylcholinesterase inhibitors and reactivators: an update on the patent literature (2012-2015). Expert Opin. Ther. Pat., 2017, 27(4), 455-476.
[] [PMID: 27967267]
Murata, K.; Matsumura, S.; Yoshioka, Y.; Ueno, Y.; Matsuda, H. Screening of β-secretase and acetylcholinesterase inhibitors from plant resources. J. Nat. Med., 2015, 69(1), 123-129.
[] [PMID: 25119528]
Roberson, E.D.; Scearce-Levie, K.; Palop, J.J.; Yan, F.; Cheng, I.H.; Wu, T.; Gerstein, H.; Yu, G.Q.; Mucke, L. Reducing endogenous tau ameliorates amyloid beta-induced deficits in an Alzheimer’s disease mouse model. Science, 2007, 316(5825), 750-754.
[] [PMID: 17478722]
Bakota, L.; Brandt, R. Tau biology and tau-directed therapies for Alzheimer’s Disease. Drugs, 2016, 76(3), 301-313.
[] [PMID: 26729186]
Mondragón-Rodríguez, S.; Perry, G.; Pena-Ortega, F.; Williams, S. Tau, amyloid beta and deep brain stimulation: aiming to restore cognitive deficit in Alzheimer’s Disease. Curr. Alzheimer Res., 2017, 14(1), 40-46.
[] [PMID: 27539594]
Merlini, M.; Wanner, D.; Nitsch, R.M. Tau pathology-dependent remodelling of cerebral arteries precedes Alzheimer’s disease-related microvascular cerebral amyloid angiopathy. Acta Neuropathol., 2016, 131(5), 737-752.
[] [PMID: 26988843]
Herrup, K. The case for rejecting the amyloid cascade hypothesis. Nat. Neurosci., 2015, 18(6), 794-799.
[] [PMID: 26007212]
Kang, S.; Lee, Y.H.; Lee, J.E. Metabolism-centric overview of the pathogenesis of Alzheimer’s Disease. Yonsei Med. J., 2017, 58(3), 479-488.
[] [PMID: 28332351]
Prasad, K.N. Oxidative stress and pro-inflammatory cytokines may act as one of the signals for regulating microRNAs expression in Alzheimer’s disease. Mech. Ageing Dev., 2017, 162, 63-71.
[] [PMID: 27964992]
Hamano, T.; Hayashi, K.; Shirafuji, N.; Nakamoto, Y. The implications of autophagy in Alzheimer’s Disease. Curr. Alzheimer Res., 2018, 15(14), 1283-1296.
[] [PMID: 30289076]
Thei, L.; Imm, J.; Kaisis, E.; Dallas, M.L.; Kerrigan, T.L. Microglia in Alzheimer’s Disease: A role for ion channels. Front. Neurosci., 2018, 12, 676.
[] [PMID: 30323735]
A., Armstrong R. Risk factors for Alzheimer’s disease. Folia Neuropathol., 2019, 57(2), 87-105.
[] [PMID: 31556570]
Nikolac Perkovic, M.; Pivac, N. Genetic Markers of Alzheimer’s Disease. Adv. Exp. Med. Biol., 2019, 1192, 27-52.
[] [PMID: 31705489]
Ahmad, S.S.; Khan, S.; Kamal, M.A.; Wasi, U. The structure and function of α, β and γ-Secretase as therapeutic target enzymes into the development of Alzheimer’s disease: A review. CNS Neurol. Disord. Drug Targets, 2019.
[] [PMID: 31608840]
Van Giau, V.; Pyun, J-M.; Suh, J.; Bagyinszky, E.; An, S.S.A.; Kim, S.Y. A pathogenic PSEN1 Trp165Cys mutation associated with early-onset Alzheimer’s disease. BMC Neurol., 2019, 19(1), 188.
[] [PMID: 31391004]
Wolfe, M.S. Structure and function of the γ-secretase complex. Biochemistry, 2019, 58(27), 2953-2966.
[] [PMID: 31198028]
Tolia, A.; Chávez-Gutiérrez, L.; De Strooper, B. Contribution of presenilin transmembrane domains 6 and 7 to a water-containing cavity in the γ-secretase complex. J. Biol. Chem., 2006, 281(37), 27633-27642.
[] [PMID: 16844686]
Telling, N.D.; Everett, J.; Collingwood, J.F.; Dobson, J.; van der Laan, G.; Gallagher, J.J.; Wang, J.; Hitchcock, A.P. Iron biochemistry is correlated with amyloid plaque morphology in an established mouse model of Alzheimer’s Disease. Cell Chem. Biol., 2017, 24(10), 1205-1215.
Lam, L.Q.; Wong, B.X.; Frugier, T.; Li, Q-X.; Collins, S.J.; Bush, A.I.; Crack, P.J.; Duce, J.A. Oxidation of Iron under physiologically relevant conditions in biological fluids from healthy and Alzheimer’s Disease subjects. ACS Chem. Neurosci., 2017, 8(4), 731-736.
[] [PMID: 28029772]
Opare, S.K.A.; Rauk, A. Copper(I) Chelators for Alzheimer’s Disease. J. Phys. Chem. B, 2017, 121(50), 11304-11310.
[] [PMID: 29172520]
Atrián-Blasco, E.; Conte-Daban, A.; Hureau, C. Mutual interference of Cu and Zn ions in Alzheimer’s disease: perspectives at the molecular level. Dalton Trans., 2017, 46(38), 12750-12759.
[] [PMID: 28937157]
Swerdlow, R.H.; Khan, S.M.A. “mitochondrial cascade hypothesis” for sporadic Alzheimer’s disease. Med. Hypotheses, 2004, 63(1), 8-20.
[] [PMID: 15193340]
Swerdlow, R.H.; Burns, J.M.; Khan, S.M. The Alzheimer’s disease mitochondrial cascade hypothesis: progress and perspectives. Biochim. Biophys. Acta, 2014, 1842(8), 1219-1231.
[] [PMID: 24071439]
Swerdlow, R.H. Mitochondria and Mitochondrial cascades in Alzheimer’s Disease. J. Alzheimers Dis., 2018, 62(3), 1403-1416.
[] [PMID: 29036828]
Swerdlow, R. H.; Burns, J. M.; Khan, S. M. The Alzheimer's disease mitochondrial cascade hypothesis. J. Alzheimer's Dis., 2010, 20(Suppl 2(Suppl 2)), S265-S279.
Onyango, I.G.; Dennis, J.; Khan, S.M. Mitochondrial dysfunction in alzheimer’s disease and the rationale for bioenergetics based therapies. Aging Dis., 2016, 7(2), 201-214.
[] [PMID: 27114851]
Swerdlow, R.H. Bioenergetics and metabolism: a bench to bedside perspective. J. Neurochem., 2016, 139(Suppl. 2), 126-135.
[] [PMID: 26968700]
UniProt: the universal protein knowledgebase. Nucleic Acids Res., 2017, 45(D1), D158-D169.
[] [PMID: 27899622]
Burley, S.K.; Berman, H.M.; Kleywegt, G.J.; Markley, J.L.; Nakamura, H.; Velankar, S. Protein Data Bank (PDB): The single global macromolecular structure archive. Methods Mol. Biol., 2017, 1607, 627-641.
[] [PMID: 28573592]
Gasteiger, E.; Gattiker, A.; Hoogland, C.; Ivanyi, I.; Appel, R.D.; Bairoch, A. ExPASy: The proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res., 2003, 31(13), 3784-3788.
[] [PMID: 12824418]
Geer, L.Y.; Marchler-Bauer, A.; Geer, R.C.; Han, L.; He, J.; He, S.; Liu, C.; Shi, W.; Bryant, S.H. The NCBI BioSystems database. Nucleic Acids Res., 2010, 38(Database issue), D492-D496.
[] [PMID: 19854944]
Bertram, L.; McQueen, M.B.; Mullin, K.; Blacker, D.; Tanzi, R.E. Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat. Genet., 2007, 39(1), 17-23.
[] [PMID: 17192785]
Sherrington, R.; Rogaev, E.I.; Liang, Y.; Rogaeva, E.A.; Levesque, G.; Ikeda, M.; Chi, H.; Lin, C.; Li, G.; Holman, K.; Tsuda, T.; Mar, L.; Foncin, J.F.; Bruni, A.C.; Montesi, M.P.; Sorbi, S.; Rainero, I.; Pinessi, L.; Nee, L.; Chumakov, I.; Pollen, D.; Brookes, A.; Sanseau, P.; Polinsky, R.J.; Wasco, W.; Da Silva, H.A.; Haines, J.L.; Perkicak-Vance, M.A.; Tanzi, R.E.; Roses, A.D.; Fraser, P.E.; Rommens, J.M.; St George-Hyslop, P.H. Cloning of a gene bearing missense mutations in early-onset familial Alzheimer’s disease. Nature, 1995, 375(6534), 754-760.
[] [PMID: 7596406]
Levy-Lahad, E.; Wasco, W.; Poorkaj, P.; Romano, D.M.; Oshima, J.; Pettingell, W.H.; Yu, C.E.; Jondro, P.D.; Schmidt, S.D.; Wang, K. Candidate gene for the chromosome 1 familial Alzheimer’s disease locus. Science, 1995, 269(5226), 973-977.
[] [PMID: 7638622]
Rogaeva, E.A.; Fafel, K.C.; Song, Y.Q.; Medeiros, H.; Sato, C.; Liang, Y.; Richard, E.; Rogaev, E.I.; Frommelt, P.; Sadovnick, A.D.; Meschino, W.; Rockwood, K.; Boss, M.A.; Mayeux, R.; St George-Hyslop, P. Screening for PS1 mutations in a referral-based series of AD cases: 21 novel mutations. Neurology, 2001, 57(4), 621-625.
[] [PMID: 11524469]
Raux, G.; Gantier, R.; Thomas-Anterion, C.; Boulliat, J.; Verpillat, P.; Hannequin, D.; Brice, A.; Frebourg, T.; Campion, D. Dementia with prominent frontotemporal features associated with L113P presenilin 1 mutation. Neurology, 2000, 55(10), 1577-1578.
[] [PMID: 11094121]
Lohmann, E.; Guerreiro, R.J.; Erginel-Unaltuna, N.; Gurunlian, N.; Bilgic, B.; Gurvit, H.; Hanagasi, H.A.; Luu, N.; Emre, M.; Singleton, A. Identification of PSEN1 and PSEN2 gene mutations and variants in Turkish dementia patients. Neurobiol. Aging, 2012, 33(8), 1850-e17.
Varela, I.; Tarpey, P.; Raine, K.; Huang, D.; Ong, C.K.; Stephens, P.; Davies, H.; Jones, D.; Lin, M.L.; Teague, J.; Bignell, G.; Butler, A.; Cho, J.; Dalgliesh, G.L.; Galappaththige, D.; Greenman, C.; Hardy, C.; Jia, M.; Latimer, C.; Lau, K.W.; Marshall, J.; McLaren, S.; Menzies, A.; Mudie, L.; Stebbings, L.; Largaespada, D.A.; Wessels, L.F.; Richard, S.; Kahnoski, R.J.; Anema, J.; Tuveson, D.A.; Perez-Mancera, P.A.; Mustonen, V.; Fischer, A.; Adams, D.J.; Rust, A.; Chan-on, W.; Subimerb, C.; Dykema, K.; Furge, K.; Campbell, P.J.; Teh, B.T.; Stratton, M.R.; Futreal, P.A. Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma. Nature, 2011, 469(7331), 539-542.
[] [PMID: 21248752]
Lao, J.I.; Beyer, K.; Fernández-Novoa, L.; Cacabelos, R. A novel mutation in the predicted TM2 domain of the presenilin 2 gene in a Spanish patient with late-onset Alzheimer’s disease. Neurogenetics, 1998, 1(4), 293-296.
[] [PMID: 10732806]
Rogaev, E.I.; Sherrington, R.; Rogaeva, E.A.; Levesque, G.; Ikeda, M.; Liang, Y.; Chi, H.; Lin, C.; Holman, K.; Tsuda, T. Familial Alzheimer’s disease in kindreds with missense mutations in a gene on chromosome 1 related to the Alzheimer’s disease type 3 gene. Nature, 1995, 376(6543), 775-778.
[] [PMID: 7651536]
Naftaly, S.; Cohen, I.; Shahar, A.; Hockla, A.; Radisky, E.S.; Papo, N. Mapping protein selectivity landscapes using multi-target selective screening and next-generation sequencing of combinatorial libraries. Nat. Commun., 2018, 9(1), 3935.
[] [PMID: 30258049]
Andrei, S.A.; Meijer, F.A.; Neves, J.F.; Brunsveld, L.; Landrieu, I.; Ottmann, C.; Milroy, L.G. Inhibition of 14-3-3/Tau by Hybrid Small-Molecule Peptides Operating via Two Different Binding Modes. ACS Chem. Neurosci., 2018, 9(11), 2639-2654.
[] [PMID: 29722962]
Johansson, P.; Kaspersson, K.; Gurrell, I.K.; Bäck, E.; Eketjäll, S.; Scott, C.W.; Cebers, G.; Thorne, P.; McKenzie, M.J.; Beaton, H.; Davey, P.; Kolmodin, K.; Holenz, J.; Duggan, M.E.; Budd Haeberlein, S.; Bürli, R.W. Toward β-Secretase-1 inhibitors with improved isoform selectivity. J. Med. Chem., 2018, 61(8), 3491-3502.
[] [PMID: 29617572]
Leung, Y.Y.; Valladares, O.; Chou, Y.F.; Lin, H.J.; Kuzma, A.B.; Cantwell, L.; Qu, L.; Gangadharan, P.; Salerno, W.J.; Schellenberg, G.D.; Wang, L.S. VCPA: genomic variant calling pipeline and data management tool for alzheimer’s disease sequencing project. Bioinformatics, 2018.
Fang, M.; Zhang, P.; Zhao, Y.; Liu, X. Bioinformatics and co-expression network analysis of differentially expressed lncRNAs and mRNAs in hippocampus of APP/PS1 transgenic mice with Alzheimer disease. Am. J. Transl. Res., 2017, 9(3), 1381-1391.
[PMID: 28386363]
Rao, A.A.; Reddi, K.K.; Thota, H. Bioinformatic analysis of Alzheimer’s disease using functional protein sequences. Bioinform. Biol. Insights, 2008, 2, 1-4.
Sun, Y.; Zhu, R.; Ye, H.; Tang, K.; Zhao, J.; Chen, Y.; Liu, Q.; Cao, Z. Towards a bioinformatics analysis of anti-Alzheimer’s herbal medicines from a target network perspective. Brief. Bioinform., 2013, 14(3), 327-343.
[] [PMID: 22887889]
Wishart, D.S.; Knox, C.; Guo, A.C.; Shrivastava, S.; Hassanali, M.; Stothard, P.; Chang, Z.; Woolsey, J. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res., 2006, 34(Database issue), D668-D672.
[] [PMID: 16381955]
Polak, S.; Wiśniowska, B.; Glinka, A.; Polak, M. a curated resource for data describing chemical triggered in vitro cardiac ion channels inhibition. BMC Pharmacol. Toxicol., 2012, 13, 6.
[] [PMID: 22947121]
Pires, D.E.V.; Blundell, T.L.; Ascher, D.B. pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. J. Med. Chem., 2015, 58(9), 4066-4072.
[] [PMID: 25860834]
Udrea, A-M.; Puia, A.; Shaposhnikov, S. AVRAM, S. Computational approaches of new perspectives in the treatment of depression during pregnancy. Farmacia, 2018, 66, 680-687.
Banerjee, P.; Eckert, A.O.; Schrey, A.K.; Preissner, R. ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Res., 2018, 46(W1), W257-W263.
[] [PMID: 29718510]
Ru, J.; Li, P.; Wang, J.; Zhou, W.; Li, B.; Huang, C.; Li, P.; Guo, Z.; Tao, W.; Yang, Y.; Xu, X.; Li, Y.; Wang, Y.; Yang, L. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J. Cheminform., 2014, 6, 13.
[] [PMID: 24735618]
Avram, S.; Buiu, C.; Duda-Seiman, D.; Duda-Seiman, C.; Borcan, F.; Mihailescu, D. Evaluation of the pharmacological descriptors related to the induction of antidepressant activity and its prediction by QSAR/QRAR methods. Mini Rev. Med. Chem., 2012, 12(6), 467-476.
[] [PMID: 22587763]
Andrade, C.H.; Pasqualoto, K.F.; Ferreira, E.I.; Hopfinger, A.J. 4D-QSAR: perspectives in drug design. Molecules, 2010, 15(5), 3281-3294.
[] [PMID: 20657478]
Avram, S.; Mihailescu, D.; Borcan, F.; Milac, A.-L. Prediction of improved antimicrobial mastoparan derivatives by 3D-QSARCoMSIA/ CoMFA and computational mutagenesis. Monatshefte für Chemie - Chemical Monthly, 2012, 143(4), 535-543.
Avram, S.; Buiu, C.; Borcan, F.; Milac, A.L. More effective antimicrobial mastoparan derivatives, generated by 3D-QSAR-Almond and computational mutagenesis. Mol. Biosyst., 2012, 8(2), 587-594.
[] [PMID: 22086548]
Lipinski, C.A. Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions. Adv. Drug Deliv. Rev., 2016, 101, 34-41.
[] [PMID: 27154268]
Benet, L.Z.; Hosey, C.M.; Ursu, O.; Oprea, T.I. BDDCS, the Rule of 5 and drugability. Adv. Drug Deliv. Rev., 2016, 101, 89-98.
[] [PMID: 27182629]
Patrick, G.L. An introduction to medicinal chemistry, 5th ed; Oxford University Press: Oxford, 2013.
Holenz, J.; Brown, D.G. Modern Lead Generation Strategies In:Lead Generation; Holenz, Ed.. Wiley-VCH: Weinheim, 2016, Vol. 68, pp. pp. 13-34.
Jena, A.B.; Calfee, J.E.; Mansley, E.C.; Philipson, T.J. ‘Me-Too’ Innovation in Pharmaceutical Markets. Forum Health Econ. Policy, 2009, 12(1), 5.
[] [PMID: 29081727]
Becker, R.E.; Seeman, M.V.; Greig, N.H.; Lahiri, D.K. What can triumphs and tribulations from drug research in Alzheimer’s disease tell us about the development of psychotropic drugs in general? Lancet Psychiatry, 2015, 2(8), 756-764.
[] [PMID: 26249306]
Speck-Planche, A.; Kleandrova, V.V.; Luan, F.; Cordeiro, M.N. Multi-target inhibitors for proteins associated with Alzheimer: in silico discovery using fragment-based descriptors. Curr. Alzheimer Res., 2013, 10(2), 117-124.
[] [PMID: 22515494]
Razzaghi-Asl, N.; Ebadi, A.; Edraki, N.; Shahabipour, S.; Miri, R. Fragment-based binding efficiency indices in bioactive molecular design: a computational approach to bace-1 inhibitors. Iran. J. Pharm. Res., 2013, 12(3), 423-436.
[PMID: 24250649]
Joshi, P.; Chia, S.; Habchi, J.; Knowles, T.P.; Dobson, C.M.; Vendruscolo, M. A Fragment-Based method of creating small-molecule libraries to target the aggregation of intrinsically disordered proteins. ACS Comb. Sci., 2016, 18(3), 144-153.
[] [PMID: 26923286]
Pandey, S.; Singh, B.K. De-novo drug design, molecular docking and in-silico molecular prediction of AChEI analogues through CADD approaches as an anti-alzheimer’s agents, Curr. Comput. Aided Drug. Des., 2020, 16, 54-72.
Chudyk, E.I.; Sarrat, L.; Aldeghi, M.; Fedorov, D.G.; Bodkin, M.J.; James, T.; Southey, M.; Robinson, R.; Morao, I.; Heifetz, A. Exploring GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method. Methods Mol. Biol., 2018, 1705, 179-195.
Shinzato, T.; Sato, R.; Suzuki, K.; Tomioka, S.; Sogawa, H.; Shulga, S.; Blume, Y.; Kurita, N. Proposal of therapeutic curcumin derivatives for Alzheimer’s disease based on ab initio molecular simulations. Chem. Phys. Lett., 2020, 738, 136883.
Lima, N.B.D.; Rocha, G.B.; Freire, R.O.; Simas, A.M. RM1 semiempirical model: chemistry, pharmaceutical research, molecular biology and materials science. J. Braz. Chem. Soc., 2019, 30, 683-716.
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]
Mezei, M. A new method for mapping macromolecular topography. J. Mol. Graph. Model., 2003, 21(5), 463-472.
[] [PMID: 12543141]
Hammes, G.G. Multiple conformational changes in enzyme catalysis. Biochemistry, 2002, 41(26), 8221-8228.
[] [PMID: 12081470]
Pagadala, N.S.; Syed, K.; Tuszynski, J. Software for molecular docking: a review. Biophys. Rev., 2017, 9(2), 91-102.
[] [PMID: 28510083]
Garzon, J.I.; Lopéz-Blanco, J.R.; Pons, C.; Kovacs, J.; Abagyan, R.; Fernandez-Recio, J.; Chacon, P. FRODOCK: a new approach for fast rotational protein-protein docking. Bioinformatics, 2009, 25(19), 2544-2551.
[] [PMID: 19620099]
Li, L.; Chen, R.; Weng, Z. RDOCK: refinement of rigid-body protein docking predictions. Proteins, 2003, 53(3), 693-707.
[] [PMID: 14579360]
Chen, R.; Li, L.; Weng, Z. ZDOCK: an initial-stage protein-docking algorithm. Proteins, 2003, 52(1), 80-87.
[] [PMID: 12784371]
Ritchie, D.W.; Kemp, G.J.L. Protein docking using spherical polar Fourier correlations. Proteins, 2000, 39(2), 178-194.
[<178:AID-PROT8>3.0.CO;2-6] [PMID: 10737939]
Jones, G.; Willett, P.; Glen, R.C.; Leach, A.R.; Taylor, R. Development and validation of a genetic algorithm for flexible docking11Edited by F. E. Cohen.J. Mol. Biol; , 1997, 267, pp. (3)727-748.
Morris, G.M.; Huey, R.; Lindstrom, W.; Sanner, M.F.; Belew, R.K.; Goodsell, D.S.; Olson, A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem., 2009, 30(16), 2785-2791.
[] [PMID: 19399780]
Korb, O.; Stützle, T.; Exner, T.E. In PLANTS: Application of Ant Colony Optimization to Structure-Based Drug Design.Berlin, Heidelberg; , 2006, pp. 247-258.
Rarey, M.; Kramer, B.; Lengauer, T.; Klebe, G. A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol., 1996, 261(3), 470-489.
[] [PMID: 8780787]
Friesner, R.A.; Banks, J.L.; Murphy, R.B.; Halgren, T.A.; Klicic, J.J.; Mainz, D.T.; Repasky, M.P.; Knoll, E.H.; Shelley, M.; Perry, J.K.; Shaw, D.E.; Francis, P.; Shenkin, P.S. Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J. Med. Chem., 2004, 47(7), 1739-1749.
[] [PMID: 15027865]
Wallace, A.C.; Laskowski, R.A.; Thornton, J.M. LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. Protein Eng., 1995, 8(2), 127-134.
[] [PMID: 7630882]
Stierand, K.; Maass, P.C.; Rarey, M. Molecular complexes at a glance: automated generation of two-dimensional complex diagrams. Bioinformatics, 2006, 22(14), 1710-1716.
[] [PMID: 16632493]
Caboche, S. LeView: automatic and interactive generation of 2D diagrams for biomacromolecule/ligand interactions. J. Cheminform., 2013, 5(1), 40-40.
[] [PMID: 23988161]
Salentin, S.; Schreiber, S.; Haupt, V.J.; Adasme, M.F.; Schroeder, M. PLIP: fully automated protein-ligand interaction profiler. Nucleic Acids Res., 2015, 43(W1), W443-7.
[] [PMID: 25873628]
Shrestha, S.; Seong, S.H.; Paudel, P.; Jung, H.A.; Choi, J.S. Structure related inhibition of enzyme systems in cholinesterases and BACE1 In Vitro by naturally occurring naphthopyrone and its glycosides isolated from Cassia obtusifolia. Molecules, 2017, 23(1), 69.
[] [PMID: 29283428]
Śledź, P.; Caflisch, A. Protein structure-based drug design: from docking to molecular dynamics. Curr. Opin. Struct. Biol., 2018, 48, 93-102.
[] [PMID: 29149726]
Liu, X.; Shi, D.; Zhou, S.; Liu, H.; Liu, H.; Yao, X. Molecular dynamics simulations and novel drug discovery. Expert Opin. Drug Discov., 2018, 13(1), 23-37.
[] [PMID: 29139324]
Lesk, A.M.; Chothia, C.H.; Blow, D.M.; Fersht, A.R.; Winter, G. The response of protein structures to amino-acid sequence changes. Philos. Trans. R. Soc. Lond. A, 1986, 317(1540), 345-356.
Hilbert, M.; Böhm, G.; Jaenicke, R. Structural relationships of homologous proteins as a fundamental principle in homology modeling. Proteins, 1993, 17(2), 138-151.
[] [PMID: 8265562]
Vyas, V.K.; Ukawala, R.D.; Ghate, M.; Chintha, C. Homology modeling a fast tool for drug discovery: current perspectives. Indian J. Pharm. Sci., 2012, 74(1), 1-17.
[] [PMID: 23204616]
Waterhouse, A.; Bertoni, M.; Bienert, S.; Studer, G.; Tauriello, G.; Gumienny, R.; Heer, F.T.; de Beer, T.A.P.; Rempfer, C.; Bordoli, L.; Lepore, R.; Schwede, T. SWISS-MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res., 2018, 46(W1), W296-W303.
[] [PMID: 29788355]
Levitt, M. Accurate modeling of protein conformation by automatic segment matching. J. Mol. Biol., 1992, 226(2), 507-533.
[] [PMID: 1640463]
Sali, A.; Blundell, T.L. Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol., 1993, 234(3), 779-815.
[] [PMID: 8254673]
Petrey, D.; Xiang, Z.; Tang, C.L.; Xie, L.; Gimpelev, M.; Mitros, T.; Soto, C.S.; Goldsmith-Fischman, S.; Kernytsky, A.; Schlessinger, A.; Koh, I.Y.; Alexov, E.; Honig, B. Using multiple structure alignments, fast model building, and energetic analysis in fold recognition and homology modeling. Proteins, 2003, 53(Suppl. 6), 430-435.
[] [PMID: 14579332]
Pieper, U.; Webb, B.M.; Dong, G.Q.; Schneidman-Duhovny, D.; Fan, H.; Kim, S.J.; Khuri, N.; Spill, Y.G.; Weinkam, P.; Hammel, M.; Tainer, J.A.; Nilges, M.; Sali, A. ModBase, a database of annotated comparative protein structure models and associated resources. Nucleic Acids Res., 2014, 42(Database issue), D336-D346.
[] [PMID: 24271400]
Muhammed, M.T.; Aki-Yalcin, E. Homology modeling in drug discovery: Overview, current applications, and future perspectives. Chem. Biol. Drug Des., 2019, 93(1), 12-20.
[] [PMID: 30187647]
Le Guilloux, V.; Schmidtke, P.; Tuffery, P. Fpocket: an open source platform for ligand pocket detection. BMC Bioinformatics, 2009, 10, 168-168.
[] [PMID: 19486540]
Volkamer, A.; Kuhn, D.; Rippmann, F.; Rarey, M. DoGSiteScorer: a web server for automatic binding site prediction, analysis and druggability assessment. Bioinformatics, 2012, 28(15), 2074-2075.
[] [PMID: 22628523]
Kawabata, T. Detection of multiscale pockets on protein surfaces using mathematical morphology. Proteins, 2010, 78(5), 1195-1211.
[] [PMID: 19938154]
Huang, B.; Schroeder, M. LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation. BMC Struct. Biol., 2006, 6, 19.
[] [PMID: 16995956]
Laurie, A.T.; Jackson, R.M. Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites. Bioinformatics, 2005, 21(9), 1908-1916.
[] [PMID: 15701681]
Levitt, D.G.; Banaszak, L.J. POCKET: a computer graphics method for identifying and displaying protein cavities and their surrounding amino acids. J. Mol. Graph., 1992, 10(4), 229-234.
[] [PMID: 1476996]
Begam, B.F.; Kumar, J.S. A Study on Cheminformatics and its Applications on Modern Drug Discovery. Procedia Eng., 2012, 38, 1264-1275.
Feng, Y.; Wang, X. Antioxidant therapies for Alzheimer’s disease. Oxid. Med. Cell. Longev., 2012, 2012, 472932-472932.
[] [PMID: 22888398]
Folch, J.; Petrov, D.; Ettcheto, M. Abad, Sánchez-López, E.; García, M. L.; Olloquequi, J.; Beas-Zarate, C.; Auladell, C.; Camins, A. Current research therapeutic strategies for alzheimer’s disease treatment. Neural Plast., 2016, 2016, 15.
Iranifar, E.; Seresht, B.M.; Momeni, F.; Fadaei, E.; Mehr, M.H.; Ebrahimi, Z.; Rahmati, M.; Kharazinejad, E.; Mirzaei, H. Exosomes and microRNAs: New potential therapeutic candidates in Alzheimer disease therapy. J. Cell. Physiol., 2019, 234(3), 2296-2305.
[] [PMID: 30191975]
Canet, G.; Chevallier, N.; Perrier, V.; Desrumaux, C.; Givalois, L. Targeting glucocorticoid receptors: A new avenue for alzheimer’s disease therapy. In: Pathology, Prevention and Therapeutics of Neurodegenerative Disease; Singh, S.; Joshi, N., Eds.; Springer: Singapore, 2019, pp. 173-183.
[ 0944-1_15]
Huang, M.; Gu, X.; Gao, X. 13 - Nanotherapeutic strategies for the treatment of neurodegenerative diseases. In: Brain Targeted Drug Delivery System; Gao, H.; Gao, X., Eds.; Academic Press: London, 2019, pp. 321-356.
[ 7.00013-5]
Renn, B.N.; Asghar-Ali, A.A.; Thielke, S.; Catic, A.; Martini, S.R.; Mitchell, B.G.; Kunik, M.E. A systematic review of practice guidelines and recommendations for discontinuation of cholinesterase inhibitors in dementia. Am. J. Geriatr. Psychiatry, 2018, 26(2), 134-147.
[] [PMID: 29167065]
Ali, T.B.; Schleret, T.R.; Reilly, B.M.; Chen, W.Y.; Abagyan, R. Adverse effects of cholinesterase inhibitors in dementia, according to the pharmacovigilance databases of the United-States and Canada. PLoS One, 2015, 10(12), e0144337.
[] [PMID: 26642212]
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]
Bajda, M.; Panek, D.; Hebda, M.; Więckowska, A.; Guzior, N.; Malawska, B. Search for potential cholinesterase inhibitors from the zinc database by virtual screening method. Acta Pol. Pharm., 2015, 72(4), 737-745.
[PMID: 26647631]
Borges, N.M.; Sartori, G.R.; Ribeiro, J.F.R.; Rocha, J.R.; Martins, J.B.L.; Montanari, C.A.; Gargano, R. Similarity search combined with docking and molecular dynamics for novel hAChE inhibitor scaffolds. J. Mol. Model., 2018, 24(1), 41.
[] [PMID: 29332299]
DrugBank. Donepezil: DB00843.. DB00843 (Accessed December, 2019).
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]
Bautista-Aguilera, O.M.; Esteban, G.; Chioua, M.; Nikolic, K.; Agbaba, D.; Moraleda, I.; Iriepa, I.; Soriano, E.; Samadi, A.; Unzeta, M.; Marco-Contelles, J. Multipotent cholinesterase/monoamine oxidase inhibitors for the treatment of Alzheimer’s disease: design, synthesis, biochemical evaluation, ADMET, molecular modeling, and QSAR analysis of novel donepezil-pyridyl hybrids. Drug Des. Devel. Ther., 2014, 8, 1893-1910.
[PMID: 25378907]
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]
Bautista-Aguilera, O.M.; Esteban, G.; Bolea, I.; Nikolic, K.; Agbaba, D.; Moraleda, I.; Iriepa, I.; Samadi, A.; Soriano, E.; Unzeta, M.; Marco-Contelles, J. Design, synthesis, pharmacological evaluation, QSAR analysis, molecular modeling and ADMET of novel donepezil-indolyl hybrids as multipotent cholinesterase/monoamine oxidase inhibitors for the potential treatment of Alzheimer’s disease. Eur. J. Med. Chem., 2014, 75, 82-95.
[] [PMID: 24530494]
Mishra, C.B.; Kumari, S.; Manral, A.; Prakash, A.; Saini, V.; Lynn, A.M.; Tiwari, M. Design, synthesis, in-silico and biological evaluation of novel donepezil derivatives as multi-target-directed ligands for the treatment of Alzheimer’s disease. Eur. J. Med. Chem., 2017, 125, 736-750.
[] [PMID: 27721157]
Khosravan, A.; Marani, S.; Sadeghi Googheri, M.S. The effects of fluorine substitution on the chemical properties and inhibitory capacity of Donepezil anti-Alzheimer drug; density functional theory and molecular docking calculations. J. Mol. Graph. Model., 2017, 71, 124-134.
[] [PMID: 27914299]
Hiremathad, A.; Chand, K.; Tolayan, L. Rajeshwari; Keri, R. S.; Esteves, A. R.; Cardoso, S. M.; Chaves, S.; Santos, M. A., Hydroxypyridinone-benzofuran hybrids with potential protective roles for Alzheimer s disease therapy. J. Inorg. Biochem., 2018, 179, 82-96.
[] [PMID: 29182921]
Dias, K.S.; de Paula, C.T.; Dos Santos, T.; Souza, I.N.; Boni, M.S.; Guimarães, M.J.; da Silva, F.M.; Castro, N.G.; Neves, G.A.; Veloso, C.C.; Coelho, M.M.; de Melo, I.S.; Giusti, F.C.; Giusti-Paiva, A.; da Silva, M.L.; Dardenne, L.E.; Guedes, I.A.; Pruccoli, L.; Morroni, F.; Tarozzi, A.; Viegas, C. Jr Design, synthesis and evaluation of novel feruloyl-donepezil hybrids as potential multitarget drugs for the treatment of Alzheimer’s disease. Eur. J. Med. Chem., 2017, 130, 440-457.
[] [PMID: 28282613]
Dias Viegas, F.P.; de Freitas Silva, M.; Divino da Rocha, M.; Castelli, M.R.; Riquiel, M.M.; Machado, R.P.; Vaz, S.M.; Simões de Lima, L.M.; Mancini, K.C.; Marques de Oliveira, P.C.; Morais, E.P.; Gontijo, V.S.; da Silva, F.M.R.; D’Alincourt da Fonseca Peçanha, D.; Castro, N.G.; Neves, G.A.; Giusti-Paiva, A.; Vilela, F.C.; Orlandi, L.; Camps, I.; Veloso, M.P.; Leomil Coelho, L.F.; Ionta, M.; Ferreira-Silva, G.A.; Pereira, R.M.; Dardenne, L.E.; Guedes, I.A.; de Oliveira Carneiro, Junior W.; Quaglio Bellozi, P.M.; Pinheiro de Oliveira, A.C.; Ferreira, F.F.; Pruccoli, L.; Tarozzi, A.; Viegas, C. Jr Design, synthesis and pharmacological evaluation of N-benzyl-piperidinyl-aryl-acylhydrazone derivatives as donepezil hybrids: Discovery of novel multi-target anti alzheimer prototype drug candidates. Eur. J. Med. Chem., 2018, 147, 48-65.
[] [PMID: 29421570]
Bellozi, P.M.Q.; Campos, A.C.; Viegas, F.P.D.; Silva, M.F.; Machado, R.P.; Vaz, S.M.; Riquiel, M.M.; Carneiro-Junior, W.O.; Lima, I.V.A.; Saliba, S.W.; Vaz, G.N.; Viegas, C., Jr; de Oliveira, A.C.P. New multifunctional AChE inhibitor drug prototypes protect against Aβ-induced memory deficit. Neurol. Sci., 2020, 41, 451-455.
[] [PMID: 31506829]
Atanasova, M.; Stavrakov, G.; Philipova, I.; Zheleva, D.; Yordanov, N.; Doytchinova, I. Galantamine derivatives with indole moiety: Docking, design, synthesis and acetylcholinesterase inhibitory activity. Bioorg. Med. Chem., 2015, 23(17), 5382-5389.
[] [PMID: 26260334]
Stavrakov, G.; Philipova, I.; Zheleva, D.; Atanasova, M.; Konstantinov, S.; Doytchinova, I. Docking-based design of galantamine derivatives with dual-site binding to acetylcholinesterase. Mol. Inform., 2016, 35(6-7), 278-285.
[] [PMID: 27492242]
Gulcan, H.O.; Orhan, I.E.; Sener, B. Chemical and molecular aspects on interactions of galanthamine and its derivatives with cholinesterases. Curr. Pharm. Biotechnol., 2015, 16(3), 252-258.
[] [PMID: 25483718]
Johnson, G.; Moore, S.W. The peripheral anionic site of acetylcholinesterase: structure, functions and potential role in rational drug design. Curr. Pharm. Des., 2006, 12(2), 217-225.
[] [PMID: 16454738]
Liu, H.; Wang, L.; Lv, M.; Pei, R.; Li, P.; Pei, Z.; Wang, Y.; Su, W.; Xie, X.Q. AlzPlatform: an Alzheimer’s disease domain-specific chemogenomics knowledgebase for polypharmacology and target identification research. J. Chem. Inf. Model., 2014, 54(4), 1050-1060.
[] [PMID: 24597646]
Wang, L.; Wang, Y.; Tian, Y.; Shang, J.; Sun, X.; Chen, H.; Wang, H.; Tan, W. Design, synthesis, biological evaluation, and molecular modeling studies of chalcone-rivastigmine hybrids as cholinesterase inhibitors. Bioorg. Med. Chem., 2017, 25(1), 360-371.
[] [PMID: 27856236]
Babitha, P.P.; Sahila, M.M.; Bandaru, S.; Nayarisseri, A.; Sureshkumar, S. Molecular docking and pharmacological investigations of rivastigmine-fluoxetine and coumarin-tacrine hybrids against acetyl choline esterase. Bioinformation, 2015, 11(8), 378-386.
[] [PMID: 26420918]
Korabecny, J.; Andrs, M.; Nepovimova, E.; Dolezal, R.; Babkova, K.; Horova, A.; Malinak, D.; Mezeiova, E.; Gorecki, L.; Sepsova, V.; Hrabinova, M.; Soukup, O.; Jun, D.; Kuca, K. 7-Methoxytacrine-p-Anisidine hybrids as novel dual binding site acetylcholinesterase inhibitors for alzheimer’s disease treatment. Molecules, 2015, 20(12), 22084-22101.
[] [PMID: 26690394]
Takahashi, H.; Xia, P.; Cui, J.; Talantova, M.; Bodhinathan, K.; Li, W.; Saleem, S.; Holland, E.A.; Tong, G.; Piña-Crespo, J.; Zhang, D.; Nakanishi, N.; Larrick, J.W.; McKercher, S.R.; Nakamura, T.; Wang, Y.; Lipton, S.A. Pharmacologically targeted NMDA receptor antagonism by Nitro Memantine for cerebrovascular disease. Sci. Rep., 2015, 5, 14781.
[] [PMID: 26477507]
Son, G.; Lee, B.I.; Chung, Y.J.; Park, C.B. Light-triggered dissociation of self-assembled β-amyloid aggregates into small, nontoxic fragments by ruthenium (II) complex. Acta Biomater., 2018, 67, 147-155.
[] [PMID: 29221856]
Currais, A.; Chiruta, C.; Goujon-Svrzic, M.; Costa, G.; Santos, T.; Batista, M.T.; Paiva, J.; do Céu Madureira, M.; Maher, P. Screening and identification of neuroprotective compounds relevant to Alzheimer׳s disease from medicinal plants of S. Tomé e Príncipe. J. Ethnopharmacol., 2014, 155(1), 830-840.
[] [PMID: 24971794]
Yang, W.T.; Zheng, X.W.; Chen, S.; Shan, C.S.; Xu, Q.Q.; Zhu, J.Z.; Bao, X.Y.; Lin, Y.; Zheng, G.Q.; Wang, Y. Chinese herbal medicine for Alzheimer’s disease: Clinical evidence and possible mechanism of neurogenesis. Biochem. Pharmacol., 2017, 141, 143-155.
[] [PMID: 28690138]
Xue, R.; Fang, Z.; Zhang, M.; Yi, Z.; Wen, C.; Shi, T. TCMID: Traditional Chinese Medicine integrative database for herb molecular mechanism analysis. Nucleic Acids Res., 2013, 41(Database issue), D1089-D1095.
[PMID: 23203875]
Ashfaq, U.A.; Mumtaz, A.; Qamar, T.U.; Fatima, T. MAPS Database: medicinal plant activities, phytochemical and structural database. Bioinformation, 2013, 9(19), 993-995.
[] [PMID: 24391364]
Pathania, S.; Bagler, G.; Ramakrishnan, S. M. Phytochemica: a platform to explore phytochemicals of medicinal plants. Database, 2015, 2015
Avram, S.; Mernea, M.; Bagci, E.; Hritcu, L.; Borcan, L.C.; Mihailescu, D.F. Advanced Structure-activity Relationships Applied to Mentha spicata L. Subsp. spicata essential oil compounds as ache and nmda ligands, in comparison with donepezil, galantamine and memantine - new approach in brain disorders pharmacology. CNS Neurol. Disord. Drug Targets, 2017, 16(7), 800-811.
[] [PMID: 28088901]
Koukoulitsa, C.; Villalonga-Barber, C.; Csonka, R.; Alexi, X.; Leonis, G.; Dellis, D.; Hamelink, E.; Belda, O.; Steele, B.R.; Micha-Screttas, M.; Alexis, M.N.; Papadopoulos, M.G.; Mavromoustakos, T. Biological and computational evaluation of resveratrol inhibitors against Alzheimer’s disease. J. Enzyme Inhib. Med. Chem., 2016, 31(1), 67-77.
[] [PMID: 26147348]
Ferlemi, A.V.; Katsikoudi, A.; Kontogianni, V.G.; Kellici, T.F.; Iatrou, G.; Lamari, F.N.; Tzakos, A.G.; Margarity, M. Rosemary tea consumption results to anxiolytic- and anti-depressant-like behavior of adult male mice and inhibits all cerebral area and liver cholinesterase activity; phytochemical investigation and in silico studies. Chem. Biol. Interact., 2015, 237, 47-57.
[] [PMID: 25910439]
Kuppusamy, A.; Arumugam, M.; George, S. Combining in silico and in vitro approaches to evaluate the acetylcholinesterase inhibitory profile of some commercially available flavonoids in the management of Alzheimer’s disease. Int. J. Biol. Macromol., 2017, 95, 199-203.
[] [PMID: 27871793]
Senol, F.S.; Ślusarczyk, S.; Matkowski, A.; Pérez-Garrido, A.; Girón-Rodríguez, F.; Cerón-Carrasco, J.P.; den-Haan, H.; Peña-García, J.; Pérez-Sánchez, H.; Domaradzki, K.; Orhan, I.E. Selective in vitro and in silico butyrylcholinesterase inhibitory activity of diterpenes and rosmarinic acid isolated from Perovskia atriplicifolia Benth. and Salvia glutinosa L. Phytochemistry, 2017, 133, 33-44.
[] [PMID: 27817931]
Awasthi, M.; Singh, S.; Pandey, V.P.; Dwivedi, U.N. Alzheimer’s disease: An overview of amyloid beta dependent pathogenesis and its therapeutic implications along with in silico approaches emphasizing the role of natural products. J. Neurol. Sci., 2016, 361, 256-271.
[] [PMID: 26810552]
Seiman, D.D.; Batalu, A.; Seiman, C.D.; Ciopec, M.; Udrea, A.M.; Motoc, M.; Negrea, A.; Avram, S. Pharmacological effects of natural compounds extracted from urtica dioica evaluated by in silico and experimental methods. Rev. Chim. Bucharest, 2018, 69, 2377-2381.
Ravi, S.K.; Ramesh, B.N.; Mundugaru, R.; Vincent, B. Multiple pharmacological activities of Caesalpinia crista against aluminium-induced neurodegeneration in rats: Relevance for Alzheimer’s disease. Environ. Toxicol. Pharmacol., 2018, 58, 202-211.
[] [PMID: 29408763]
Jomova, K.; Lawson, M.; Drostinova, L.; Lauro, P.; Poprac, P.; Brezova, V.; Michalik, M.; Lukes, V.; Valko, M. Protective role of quercetin against copper(II)-induced oxidative stress: A spectroscopic, theoretical and DNA damage study. Food Chem. Toxicol., 2017, 110, 340-350.
[] [PMID: 29107026]
Gibellini, L.; Bianchini, E.; De Biasi, S.; Nasi, M.; Cossarizza, A.; Pinti, M. Natural Compounds Modulating Mitochondrial Functions. Evidence-based complementary and alternative medicine : eCAM, 2015, 2015 , 527209-527209.
Alberdi, E.; Sánchez-Gómez, M.V.; Ruiz, A.; Cavaliere, F.; Ortiz-Sanz, C.; Quintela-López, T.; Capetillo-Zarate, E.; Solé-Domènech, S.; Matute, C. Mangiferin and morin attenuate oxidative stress, mitochondrial dysfunction, and neurocytotoxicity, induced by amyloid beta oligomers. Oxid. Med. Cell. Longev., 2018, 2018, 2856063.
Yang, X-X.; Zhou, Y-Z.; Xu, F.; Yu, J. Gegentana; Shang, M.Y.; Wang, X.; Cai, S.Q. Screening potential mitochondria-targeting compounds from traditional Chinese medicines using a mitochondria-based centrifugal ultrafiltration/liquid chromatography/mass spectrometry method. J. Pharm. Anal., 2018, 8(4), 240-249.
[] [PMID: 30140488]
Velander, P.; Wu, L.; Henderson, F.; Zhang, S.; Bevan, D.R.; Xu, B. Natural product-based amyloid inhibitors. Biochem. Pharmacol., 2017, 139, 40-55.
[] [PMID: 28390938]
Rao, P.P.; Mohamed, T.; Teckwani, K.; Tin, G. Curcumin binding to beta amyloid: a computational study. Chem. Biol. Drug Des., 2015, 86(4), 813-820.
[] [PMID: 25776887]
Berhanu, W.M.; Masunov, A.E. Atomistic mechanism of polyphenol amyloid aggregation inhibitors: molecular dynamics study of curcumin, exifone, and myricetin interaction with the segment of tau peptide oligomer. J. Biomol. Struct. Dyn., 2015, 33(7), 1399-1411.
[] [PMID: 25093402]
Landau, M.; Sawaya, M.R.; Faull, K.F.; Laganowsky, A.; Jiang, L.; Sievers, S.A.; Liu, J.; Barrio, J.R.; Eisenberg, D. Towards a pharmacophore for amyloid. PLoS Biol., 2011, 9(6), e1001080.
[] [PMID: 21695112]
Nedumpully-Govindan, P.; Kakinen, A.; Pilkington, E.H.; Davis, T.P.; Chun Ke, P.; Ding, F. Stabilizing off-pathway oligomers by polyphenol nanoassemblies for iapp aggregation inhibition. Sci. Rep., 2016, 6, 19463.
[] [PMID: 26763863]
Mo, Y.; Lei, J.; Sun, Y.; Zhang, Q.; Wei, G. Conformational Ensemble of hIAPP Dimer: Insight into the molecular mechanism by which a green tea extract inhibits hiapp aggregation. Sci. Rep., 2016, 6, 33076.
[] [PMID: 27620620]
Stefanachi, A.; Leonetti, F.; Pisani, L.; Catto, M.; Carotti, A. Coumarin: A natural, privileged and versatile scaffold for bioactive compounds. Molecules, 2018, 23(2), E250.
[] [PMID: 29382051]
Hamulakova, S.; Poprac, P.; Jomova, K.; Brezova, V.; Lauro, P.; Drostinova, L.; Jun, D.; Sepsova, V.; Hrabinova, M.; Soukup, O.; Kristian, P.; Gazova, Z.; Bednarikova, Z.; Kuca, K.; Valko, M. Targeting copper(II)-induced oxidative stress and the acetylcholinesterase system in Alzheimer’s disease using multifunctional tacrine-coumarin hybrid molecules. J. Inorg. Biochem., 2016, 161, 52-62.
[] [PMID: 27230386]

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