Therapeutic Potential of Amyloid‐β Interactors in Rapidly Progressive Alzheimer's Disease—An In Silico Study

Rapidly progressive Alzheimer's disease (rpAD) is a rare but severe form of Alzheimer's disease characterized by accelerated cognitive decline and limited therapeutic options. Conventional anti–amyloid‐β interventions have shown little success due to poor target specificity, neurotoxicity, and lack of efficacy, underscoring the need for novel therapeutic strategies. This study aimed to identify and prioritize molecular targets associated with rpAD by investigating the protein interactome of amyloid‐β (Aβ 42 ) using integrative computational approaches. Functional enrichment, protein–protein interaction network analysis, and community clustering revealed that rpAD‐specific Aβ 42 interactors were predominantly involved in mitochondrial bioenergetics, redox regulation, and cytoskeletal stability, pathways central to neuronal survival and synaptic function. Molecular docking identified fumarate hydratase, carbonyl reductase 1, and the F‐actin capping protein as high‐affinity interactors of Aβ 42 , linking these proteins to energy failure, oxidative stress, and synaptic dysfunction. Virtual screening of a therapeutic drug library against fumarate hydratase identified several compounds with strong binding affinities, among which quinestrol, estradiol benzoate, norethindrone, tamibarotene, drospirenone, and ketanserin emerged as lead candidates. Pharmacokinetic profiling, including ADMET modeling, confirmed their blood–brain barrier permeability and drug‐likeness, supporting their potential as central nervous system active agents. Together, this work highlights key molecular targets in rpAD and proposes repurposed, pharmacologically diverse compounds with multitarget neuroprotective potential. By utilizing in silico analysis, the study provides a rational framework for target discovery and drug prioritization in rpAD, offering a foundation for future experimental validation and the development of translational research.