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Alzheimer's disease (AD) is a neurodegenerative disorder marked by a decline in cognitive function and memory loss, primarily resulting from cholinergic dysfunction, the accumulation of amyloid plaques, the formation of tau tangles, and the progressive degeneration of neurons. While existing treatments offer limited symptomatic relief, they do not effectively halt or reverse the underlying progression of the disease, presenting a major global challenge in Alzheimer’s research. Developing therapeutic strategies for AD remains complex, largely due to the inability of current medications to significantly slow neurodegeneration. Traditional drug discovery processes are often lengthy, costly, and inefficient, further complicating the search for effective treatments. To overcome these obstacles, researchers have turned to a combination of computational approaches alongside conventional drug design techniques. These integrated methodologies help accelerate the discovery process by significantly reducing both time and costs. This review delves into the underlying physiological and pathological mechanisms of Alzheimer's disease, while identifying potential drug targets such as acetylcholinesterase, butyrylcholinesterase, β-Secretase (BACE-1), A2A adenosine receptor, Dickkopf-1 protein, glycogen synthase kinase-3β, indoleamine 2,3-dioxygenase, monoamine oxidase-B, NMDA receptor, Wnt inhibitory factor, cyclin-dependent kinase-5, glutaminyl cyclase, and cathepsin-B. Furthermore, the review examines various computer-aided drug design (CADD) methodologies, including structure-based and ligand-based approaches, virtual screening, pharmacophore modeling, molecular modelling, and simulation techniques. These computational strategies are playing an increasingly important role in Alzheimer’s research, particularly in drug discovery. By investigating promising drug candidates and lead molecules that target key proteins involved in Alzheimer’s pathogenesis, the review highlights their binding modes with these targets and assesses the chemical properties essential for the development of effective clinical candidates. The aim is to provide researchers with critical insights and tools to design novel compounds with the necessary chemical and physical characteristics required for the successful treatment of Alzheimer’s disease.
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