Title:Conventional and Emerging Drug Targeting Sites in Alzheimer’s Disease and the Role of Translational Informatics in its Diagnosis and Management
Volume: 23
Issue: 14
Author(s): Kashif Ali Khan, Muhammad Esa, Zul Kamal, Bashir Ullah*, George Perry, Shah Kamal, Shujaat Ahmad, Haya Hussain, Abid Ullah and Muhammad Shafique*
Affiliation:
- Department of Pharmacy, Shaheed Benazir Bhutto University, Sheringal 18500, Khyber Pakhtunkhwa, Pakistan
- Department of Pharmaceutics, College of Pharmacy, Shaqra University, Shaqra 11961,
Saudi Arabia
Keywords:
Alzheimer’s disease (AD), amyloid-β plaques, novel drug-targeting sites, translational informatics, explainable artificial intelligence (AI), multimodal approaches.
Abstract: Alzheimer’s disease (AD), a neurodegenerative condition, continues to pose significant
challenges to modern medicine due to the limited efficacy offered by current therapeutic modalities.
With the complex pathophysiology of AD, which includes tau protein accumulation, amyloid-β
plaque formation, neuroinflammation, and synaptic dysfunction, novel drug-targeting sites must be
identified. This study presents a thorough evaluation of novel drug targeting sites, with a focus on
these pathological characteristics as promising therapeutic targets while providing an explanation of
their role in the course of the disease. We investigate in detail how neurotoxicity, resulting in synapse
failure and cognitive impairment, is caused by tau proteins and amyloid plaques. In addition,
the article discusses the increasing evidence that synaptic dysfunction is a major factor in the disease's
progression, as well as the significance of neuroinflammation in the pathophysiology of the
condition. The review also covers new drug sites such as amyloid-β plaques, tau proteins, and the inhibition
of neuroinflammation mediators, in addition to traditional drug sites, including cholinergic
and glutamatergic therapeutic targets. Lastly, we discuss the role of translational informatics involving
data modeling, predictive analytics, explainable artificial intelligence (AI), and multimodal approaches
for the management and prediction of AD. This article will serve as a guide for future research
efforts in the fields of neuroscience, neuropharmacology, drug delivery sciences, and translational
informatics.
