Generic placeholder image

Combinatorial Chemistry & High Throughput Screening


ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Review Article

A Comprehensive Computational Perspective in Drug Discovery for Alzheimer's Disease

Author(s): Manikandan Selvaraj, Karthik Sadasivam, Muralidharan Jothimani and Karthikeyan Muthusamy*

Volume 26, Issue 12, 2023

Published on: 17 October, 2022

Page: [2113 - 2123] Pages: 11

DOI: 10.2174/1386207325666220606142910

Price: $65


Alzheimer's Disease (AD), the most common and major disability issue in our society, has a substantial economic impact. Despite substantial advances in aetiology, diagnosis, and therapy, the fundamental causes of the disease remain unknown, accurate biomarkers are not well characterized, and current pharmaceutical medications are not cost-effective. Effective care for Alzheimer's disease and other types of dementia is crucial for patients' long-term health. Pathogenesis advances have aroused the scientific community's interest in the creation of new pharmacological treatments that target recognized disease targets throughout the previous two decades. Pharmacological therapy has recently been assigned 10 - 20% of the direct costs of AD. Less than 20% of Alzheimer's patients respond somewhat to standard medicines with questionable cost-effectiveness (donepezil, galantamine, memantine and rivastigmine). Therefore, currently known treatment approaches address the condition indirectly, as acetyl cholinesterase related inhibitors and the Nmethyl d-aspartate as receptor and antagonists have little effect on the sickness. Novel targets and specific small molecules must also be found in order to be useful in the therapy of AD. This chapter examines a wide spectrum of Alzheimer's disease targets as well as contemporary progress in the discovery of disease inhibitors. In addition, brief in-silico investigations were highlighted and provided to understand how the theoretical lead in AD treatment development is attainable.

Keywords: Alzheimer's disease, pharmacological therapy, dementia, donepezil, Parkinson's disease, memory loss.

Graphical Abstract
Cutsuridis, V.; Moustafa, A. Computational models of Alzheimer’s disease. Scholarpedia J., 2017, 12(1), 32144.
Ganau, S.G.; Services, E.A. Chapter 2 recent advances in computational approaches; , 2018.
Petrella, JR.; Hao, W.; Rao, A.; Doraiswamy, PM.; Li, S. Computational causal modeling of the dynamic biomarker cascade in Alzheimer’s disease. Comput. Math. Methods Med., 2019, 2019, 6216530.
Caligiore, D.; Silvetti, M.; D’Amelio, M.; Puglisi-Allegra, S.; Baldassarre, G.; Anbarjafari, G. Computational modeling of catecholamines dysfunction in Alzheimer’s disease at pre-plaque stage. J. Alzheimers Dis., 2020, 77(1), 275-290.
[] [PMID: 32741822]
Beltrán, J.; García-Vázquez, MS.; Benois-Pineau, J.; Gutierrez-Robledo, LM.; Dartigues, JF. Computational techniques for eye movements analysis towards supporting early diagnosis of Alzheimer’s disease: A review. Comput. Math. Methods Med., 2018, 2018, 2676409.
Kaufer, D.; Gandy, S. APOE ε4 and bapineuzumab: Infusing pharmacogenomics into Alzheimer disease therapeutics. Neurology, 2009, 73(24), 2052-2053.
[] [PMID: 19923549]
Mucke, L. Lots of people are forgetful. Are there any particular warning signs of Alzheimer’s disease? Neuroscience, 2009, 461(October), 895-897. [Internet}
Rycroft, S.S.; Giovannetti, T. Alzheimer’s disease and other dementia disorders. In: Changes in the Brain: Impact on Daily Life; , 2016; pp. 37-63.
Sandeep Reddy, C.H.; Sree Kumar Reddy, G.; Mahto, M.K.; Kunala, P.; Chaitanya Kanth, R. In silico design and discovery of some novel ache inhibitors for treatment of Alzheimer’s disorder. Res. J. Pharm. Technol., 2012, 5(3), 424-427.
Kim, O.Y.; Song, J. The role of irisin in Alzheimer’s disease. J. Clin. Med., 2018, 7(11), 407.
[] [PMID: 30388754]
Leuzy, A.; Heurling, K.; Ashton, N.J.; Schöll, M.; Eduardo, R. In vivo detection of Alzheimer’s disease. Yalle J. Biol. Med., 2018, 91, 291-300.
2016 Alzheimer’s disease facts and figures. Alzheimers Dement., 2016, 12(4), 459-509.
[] [PMID: 27570871]
Khachaturian, Z.S. Diagnosis of Alzheimer’s disease. Arch. Neurol., 1985, 42(11), 1097-1105.
[] [PMID: 2864910]
Godoy, J.A.; Rios, J.A.; Zolezzi, J.M.; Braidy, N.; Inestrosa, N.C. Signaling pathway cross talk in Alzheimer’s disease. Cell Commun. Signal., 2014, 12(1), 23.
[] [PMID: 24679124]
Tai, L.M.; Balu, D.; Avila-Munoz, E.; Abdullah, L.; Thomas, R.; Collins, N.; Valencia-Olvera, A.C.; LaDu, M.J. EFAD transgenic mice as a human APOE relevant preclinical model of Alzheimer’s disease. J. Lipid Res., 2017, 58(9), 1733-1755.
[] [PMID: 28389477]
Jonsson, T.; Atwal, J.K.; Steinberg, S.; Snaedal, J.; Jonsson, P.V.; Bjornsson, S.; Stefansson, H.; Sulem, P.; Gudbjartsson, D.; Maloney, J.; Hoyte, K.; Gustafson, A.; Liu, Y.; Lu, Y.; Bhangale, T.; Graham, R.R.; Huttenlocher, J.; Bjornsdottir, G.; Andreassen, O.A.; Jönsson, E.G.; Palotie, A.; Behrens, T.W.; Magnusson, O.T.; Kong, A.; Thorsteinsdottir, U.; Watts, R.J.; Stefansson, K. A mutation in APP protects against Alzheimer’s disease and age-related cognitive decline. Nature, 2012, 488(7409), 96-99.
[] [PMID: 22801501]
Mohler, E.G.; Baker, P.M.; Gannon, K.S.; Jones, S.S.; Shacham, S.; Sweeney, J.A.; Ragozzino, M.E. The effects of PRX-07034, a novel 5-HT6 antagonist, on cognitive flexibility and working memory in rats. Psychopharmacology (Berl.), 2012, 220(4), 687-696.
[] [PMID: 21989804]
Zhu Xiongwei Oxidative stress signalling in Alzheimer's disease. Brain Res., 2004, 1-2(2004), 32-39.
Shinohara, M.; Tachibana, M.; Kanekiyo, T.; Bu, G. Role of LRP1 in the pathogenesis of Alzheimer’s disease: Evidence from clinical and preclinical studies. J. Lipid Res., 2017, 58(7), 1267-1281.
[] [PMID: 28381441]
Herz, J.; Strickland, D.K. Fundacja PlasticsEurope Polska., 2001, 108(6), 779-784.
Šimić, G.; Babić Leko, M.; Wray, S.; Harrington, C.; Delalle, I.; Jovanov-Milošević, N.; Bažadona, D.; Buée, L.; de Silva, R.; Di Giovanni, G.; Wischik, C.; Hof, P.R. Tau protein hyperphosphorylation and aggregation in Alzheimer’s disease and other tauopathies, and possible neuroprotective strategies. Biomolecules, 2016, 6(1), 6.
[] [PMID: 26751493]
Mandelkow, E.M.; Mandelkow, E. Biochemistry and cell biology of tau protein in neurofibrillary degeneration. Cold Spring Harb. Perspect. Med., 2012, 2(7), a006247.
[] [PMID: 22762014]
He, G.; Luo, W.; Li, P.; Remmers, C.; Netzer, W.J.; Hendrick, J.; Bettayeb, K.; Flajolet, M.; Gorelick, F.; Wennogle, L.P.; Greengard, P. Gamma-secretase activating protein is a therapeutic target for Alzheimer’s disease. Nature, 2010, 467(7311), 95-98.
[] [PMID: 20811458]
Borgegard, T.; Juréus, A.; Olsson, F.; Rosqvist, S.; Sabirsh, A.; Rotticci, D.; Paulsen, K.; Klintenberg, R.; Yan, H.; Waldman, M.; Stromberg, K.; Nord, J.; Johansson, J.; Regner, A.; Parpal, S.; Malinowsky, D.; Radesater, A.C.; Li, T.; Singh, R.; Eriksson, H.; Lundkvist, J. First and second generation γ-secretase modulators (GSMs) modulate amyloid-β (Aβ) peptide production through different mechanisms. J. Biol. Chem., 2012, 287(15), 11810-11819.
[] [PMID: 22334705]
Guideline on the clinical investigation of medicines for the treatment of Alzheimer’s disease., 2015, 1-36. Available from:
Anbarasu, A.; Kundu, A. In silico study of Alzheimer’s disease in relation to FYN gene. Interdiscip. Sci., 2012, 4(2), 153-160.
[] [PMID: 22843238]
Singh, K.D.; Muthusamy, K. Molecular modeling, quantum polarized ligand docking and structure-based 3D-QSAR analysis of the imidazole series as dual AT(1) and ET(A) receptor antagonists. Acta Pharmacol. Sin., 2013, 34(12), 1592-1606.
[] [PMID: 24304920]
Walz, W. Computational modeling of drugs against Alzheimer’s disease. 2018, 132, 249-261.
Rawat, A.K. Computer - aided diagnosis of Alzheimer’s disease : A review. 2018.
de Haan, W.; van Straaten, E.C.W.; Gouw, A.A.; Stam, C.J. Altering neuronal excitability to preserve network connectivity in a computational model of Alzheimer’s disease. PLOS Comput. Biol., 2017, 13(9), e1005707.
[] [PMID: 28938009]
Ding, X.; Bucholc, M.; Wang, H.; Glass, D.H.; Wang, H.; Clarke, D.H.; Bjourson, A.J.; Dowey, L.R.C.; O’Kane, M.; Prasad, G.; Maguire, L.; Wong-Lin, K. A hybrid computational approach for efficient Alzheimer’s disease classification based on heterogeneous data. Sci. Rep., 2018, 8(1), 9774.
[] [PMID: 29950585]
Fung, G.; Stoeckel, J. SVM feature selection for classification of SPECT images of Alzheimer’s disease using spatial information. Knowl. Inf. Syst., 2007, 11(2), 243-258.
Zhu, Y.; Zhu, X.; Kim, M.; Shen, D.; Wu, G. Early diagnosis of Alzheimer’s disease by joint feature selection and classification on temporally structured support vector machine. International Conference on Medical Image Computing and Computer-Assisted Intervention, 2016.
Loganathan, L.; Natarajan, K.; Muthusamy, K. Computational study on cross-talking cancer signalling mechanism of ring finger protein 146, AXIN and Tankyrase protein complex. J. Biomol. Struct. Dyn., 2020, 38(17), 5173-5185.
[] [PMID: 31760854]
Dhanachandra Singh, K.; Jajodia, A.; Kaur, H.; Kukreti, R.; Karthikeyan, M. Gender specific association of RAS gene polymorphism with essential hypertension: A case-control study. Biomed. Res. Int., 2014, 2014, 538053.
Muthusamy, K.; Prasad, S.; Nagamani, S. Role of hydrophobic patch in LRP6: A promising drug target for Alzheimer’s disease. Indian J. Pharm. Sci., 2016, 78(2), 240-251.
Florian, H.; Meier, A.; Gauthier, S.; Lipschitz, S.; Lin, Y.; Tang, Q.; Othman, A.A.; Robieson, W.Z.; Gault, L.M. al. Efficacy and safety of ABT-126 in subjects with mild-to-moderate Alzheimer’s disease on stable doses of acetylcholinesterase inhibitors: A randomized, double-blind, placebo-controlled study. J. Alzheimers Dis., 2016, 51(4), 1237-1247.
[] [PMID: 26967214]
Schaffhauser, H.; Mathiasen, J.R.; Dicamillo, A.; Huffman, M.J.; Lu, L.D.; McKenna, B.A.; Qian, J.; Marino, M.J. Dimebolin is a 5-HT6 antagonist with acute cognition enhancing activities. Biochem. Pharmacol., 2009, 78(8), 1035-1042.
[] [PMID: 19549510]
Cifuentes, R.A.; Murillo-Rojas, J. Alzheimer’s disease and HLA-A2: Linking neurodegenerative to immune processes through an in silico approach. Biomed. Res. Int., 2014, 2014, 791238.
Greco, I.; Day, N.; Riddoch-Contreras, J.; Reed, J.; Soininen, H.; Kłoszewska, I.; Tsolaki, M.; Vellas, B.; Spenger, C.; Mecocci, P.; Wahlund, L.O.; Simmons, A.; Barnes, J.; Lovestone, S. Alzheimer’s disease biomarker discovery using in silico literature mining and clinical validation. J. Transl. Med., 2012, 10(1), 217.
[] [PMID: 23113945]
Herrik, K.F.; Mørk, A.; Richard, N.; Bundgaard, C.; Bastlund, J.F.; de Jong, I.E.M. The 5-HT6 receptor antagonist idalopirdine potentiates the effects of acetylcholinesterase inhibition on neuronal network oscillations and extracellular acetylcholine levels in the rat dorsal hippocampus. Neuropharmacology, 2016, 107, 351-363.
[] [PMID: 27039041]

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