A Comprehensive Computational Perspective in Drug Discovery for Alzheimer's Disease

Abstract

Alzheimer's Disease (AD), the most common and major disability issue in our society, has a substantial economic impact. Despite substantial advances in aetiology, diagnosis, and therapy, the fundamental causes of the disease remain unknown, accurate biomarkers are not well characterized, and current pharmaceutical medications are not cost-effective. Effective care for Alzheimer's disease and other types of dementia is crucial for patients' long-term health. Pathogenesis advances have aroused the scientific community's interest in the creation of new pharmacological treatments that target recognized disease targets throughout the previous two decades. Pharmacological therapy has recently been assigned 10 - 20% of the direct costs of AD. Less than 20% of Alzheimer's patients respond somewhat to standard medicines with questionable cost-effectiveness (donepezil, galantamine, memantine and rivastigmine). Therefore, currently known treatment approaches address the condition indirectly, as acetyl cholinesterase related inhibitors and the Nmethyl d-aspartate as receptor and antagonists have little effect on the sickness. Novel targets and specific small molecules must also be found in order to be useful in the therapy of AD. This chapter examines a wide spectrum of Alzheimer's disease targets as well as contemporary progress in the discovery of disease inhibitors. In addition, brief in-silico investigations were highlighted and provided to understand how the theoretical lead in AD treatment development is attainable.

Keywords: Alzheimer's disease; Parkinson's disease; dementia; donepezil; memory loss; pharmacological therapy.