A comprehensive computational perspective in drug discovery for Alzheimer's disease.

Abstract

Abstract: Alzheimer's disease (AD), the most common serious and disability issue with a significant economic impact on our society. Despite significant improvements in an etiology, diagnosis, and therapy, its underlying causes are still unknown, reliable biomarkers are not clearly defined, and current pharmaceutical therapies are not cost-effective. Effective care of AD and other dementia types are critical in patients for their healthy lifespan. Over the last two decades, developments in pathogenesis have piqued the interest of the scientific community in the development of new pharmacological treatments that target recognized disease targets. Pharmacological therapy has been recently ascribed to 10 - 20% of the direct expenses 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 N-methyl d-aspartate as receptor and as 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 considers a wide range targets for Alzheimer's disease and current advances in the discovery of disease inhibitors. And also brief in-silico studies were highlighted and included to know how the theoretical lead is achievable in AD medication discovery.