Alzheimer’s disease (AD) is the most common form of dementia, characterized by progressive memory loss and cognitive decline. Its key pathological hallmarks include extracellular amyloid plaques composed of amyloid beta (Aβ) peptides and intracellular neurofibrillary tangles formed by hyperphosphorylated tau protein. Although numerous studies have investigated the complex pathology of AD, its underlying mechanisms remain incompletely understood. The amyloid cascade hypothesis continues to be the leading model of AD pathogenesis. It suggests that Aβ aggregation is the initial trigger of neurotoxicity, setting off a cascade of pathological events including inflammation, oxidative stress, tau hyperphosphorylation, synaptic dysfunction, and, ultimately, dementia. Molecular dynamics (MD) is a powerful tool in structure-based drug design (SBDD). By simulating biomolecular motions at the atomic level, MD provides unique insights into molecular properties, functions, and inhibition mechanisms—insights often inaccessible through other experimental or computational techniques. When integrated with experimental data, MD further deepens our understanding of molecular interactions and biological processes. Natural compounds, known for their pleiotropic pharmacological activities, favorable safety profiles, and general tolerability (despite occasional side effects), are increasingly explored for their potential in both the treatment and prevention of various diseases, including AD. In this review, we summarize current findings from MD simulations of natural compounds with anti-amyloidogenic potential. This work builds upon our previous publication, which focused on endogenous compounds and repurposed drugs. The review is structured as follows: an overview of the amyloid cascade hypothesis; a discussion of Aβ oligomeric structures and their stabilizing interactions; a section on molecular dynamics, including its challenges and future directions; and a comprehensive analysis of the inhibitory mechanisms of natural compounds, categorized by their shared structural features.
Mariyana Atanasova (Sun,) studied this question.