Computer-Aided Multi-Target Management of Emergent Alzheimer's Disease

Overview

Journal Bioinformation

Specialty Biology

Date 2018 Jul 10

PMID 29983487

Citations 1

Authors

Hyunjo Kim

HyunWook Han

Affiliations

Soon will be listed here.

Abstract

Alzheimer's disease (AD) represents an enormous global health burden in terms of human suffering and economic cost. AD management requires a shift from the prevailing paradigm targeting pathogenesis to design and develop effective drugs with adequate success in clinical trials. Therefore, it is of interest to report a review on amyloid beta (Aβ) effects and other multi-targets including cholinesterase, NFTs, tau protein and TNF associated with brain cell death to be neuro-protective from AD. It should be noted that these molecules have been generated either by target-based or phenotypic methods. Hence, the use of recent advancements in nanomedicine and other natural compounds screening tools as a feasible alternative for circumventing specific liabilities is realized. We review recent developments in the design and identification of neuro-degenerative compounds against AD generated using current advancements in computational multi-target modeling algorithms reflected by theragnosis (combination of diagnostic tests and therapy) concern.

Citing Articles

Computer-Aided Drug Design of β-Secretase, γ-Secretase and Anti-Tau Inhibitors for the Discovery of Novel Alzheimer's Therapeutics.

Mouchlis V, Melagraki G, Zacharia L, Afantitis A Int J Mol Sci. 2020; 21(3).

PMID: 31973122 PMC: 7038192. DOI: 10.3390/ijms21030703.

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