Alzheimer's disease (AD) is an age-related neurodegenerative disorder that accounts for numerous deaths worldwide. AD is the most common cause of dementia, characterized by accumulation of fibrous amyloid beta protein in the brain with clinical symptoms, such as loss of intellectual and social skills, gradually leading to the death of brain cells. The genetic complexity of AD during disease progression requires a systems-level understanding to design viable therapeutics. We present an integrative computational analysis to prioritize AD-associated genes outlined through a protein-protein interaction network. Multiple topological parameters of the network were considered to target proteins which are accountable for disease susceptibility. Furthermore, in silico protein structure modeling and molecular dynamics simulation approaches were implemented to characterize presenilin 2 (PSEN2) protein as one of the leading targets in the network. The findings are constructive to aid future drug discovery endeavors in the treatment of AD.
Keywords: Alzheimer's disease; drug target; molecular dynamics; protein interaction network; structure prediction; topological vulnerability.