Alzheimer's disease (AD) stands as the predominant contributor to dementia cases. The ongoing developments in our understanding of its pathogenesis have sparked the interest of researchers, driving them to explore innovative treatment approaches. Existing therapies incorporating cholinesterase inhibitors and/or NMDA antagonists have shown limited improvement in alleviating symptoms. This, in turn, highlights the urgency for the pursuit of more effective therapeutic options. Given the annual rise in the number of individuals affected by dementia, it is imperative to allocate resources and efforts towards the exploration of novel therapeutic options. This review aims to provide a comprehensive overview of the AD-related hypotheses, along with the computational approaches employed in research within each hypothesis. In this comprehensive review, the authors shed light on using various computational tools, including diverse case studies, in the pursuit of finding efficacious treatments for AD. The development of more sophisticated diagnostic techniques is crucial, enabling early detection and intervention in the battle against this challenging condition. The potential treatments investigated in this analysis are poised to assume ever more significant functions in both preventing and treating AD, ultimately enhancing the management of the condition and the overall well-being of individuals affected by AD.

Center for Natural and Human Sciences Federal University of ABC Santo André 09280 560 Brazil

Department of Chemistry Faculty of Science University of Hradec Kralove Hradec Kralove Czech Republic

Department of Chemistry Federal University of Lavras Lavras 37200 000 Brazil

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