Title

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

Authors

Hyunjo Kim^1,2,3 & Hyunwook Han^2,3,4,*

Affiliation

¹Department of Medical Informatics, Ajou Medical University Hospital, Suwon, Kyeounggido province, South Korea;

²Department of Informatics, School of Medicine, CHA University, Seongnam, South Korea;

³Institute of Basic Medical Sciences, School of Medicine, CHA University, Seongnam, South Korea; ⁴BioMedical Informatics, CHA Medical University Hospital, Seongnam, Kyeounggido province, South Korea;

Email

hyunjokim@hotmail.com

Article Type

Review

Date

Received March 27, 2018; Revised April 29, 2018 Accepted April 30, 2018; Published May 05, 2018

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.

Keywords

Alzheimer's disease, treatment modeling algorithms, memory complications, chronic neuro-degenerative disorder, dementia prediction, theragnosis

Citation

Kim & Han. Bioinformation 14(4): 167-180 (2018)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.