A Drug Repositioning Approach Reveals Ergotamine May Be a Potential Drug for the Treatment of Alzheimer's Disease.

Alzheimer’s disease drug repositioning ergotamine molecular docking risk genes

Journal

Journal of Alzheimer's disease : JAD
ISSN: 1875-8908
Titre abrégé: J Alzheimers Dis
Pays: Netherlands
ID NLM: 9814863

Informations de publication

Date de publication:
12 Sep 2024
Historique:
medline: 13 9 2024
pubmed: 13 9 2024
entrez: 13 9 2024
Statut: aheadofprint

Résumé

Alzheimer's disease (AD) is a neurodegenerative disorder that is the most common form of dementia in the elderly. The drugs currently used to treat AD only have limited effects and are not able to cure the disease. Drug repositioning has increasingly become a promising approach to find potential drugs for diseases like AD. To screen potential drug candidates for AD based on the relationship between risk genes of AD and drugs. We collected the risk genes of AD and retrieved the information of known drugs from DrugBank. Then, the AD-related genes and the targets of each drug were mapped to the human protein-protein interaction network (PPIN) to represent AD and the drugs on the network. The network distances between each drug and AD were calculated to screen the drugs proximal to AD-related genes on PPIN, and the screened drug candidates were further analyzed by molecular docking and molecular dynamics simulations. We compiled a list of 714 genes associated with AD. From 5,833 drugs used for human diseases, we identified 1,044 drugs that could be potentially used to treat AD. Then, amyloid-β (Aβ) protein, the key molecule involved in the pathogenesis of AD was selected as the target to further screen drugs that may inhibit Aβ aggregation by molecular docking. We found that ergotamine and RAF-265 could bind stably with Aβ. In further analysis by molecular dynamics simulations, both drugs exhibited reasonable stability. Our work indicated that ergotamine and RAF-265 may be potential candidates for treating AD.

Sections du résumé

Background UNASSIGNED
Alzheimer's disease (AD) is a neurodegenerative disorder that is the most common form of dementia in the elderly. The drugs currently used to treat AD only have limited effects and are not able to cure the disease. Drug repositioning has increasingly become a promising approach to find potential drugs for diseases like AD.
Objective UNASSIGNED
To screen potential drug candidates for AD based on the relationship between risk genes of AD and drugs.
Methods UNASSIGNED
We collected the risk genes of AD and retrieved the information of known drugs from DrugBank. Then, the AD-related genes and the targets of each drug were mapped to the human protein-protein interaction network (PPIN) to represent AD and the drugs on the network. The network distances between each drug and AD were calculated to screen the drugs proximal to AD-related genes on PPIN, and the screened drug candidates were further analyzed by molecular docking and molecular dynamics simulations.
Results UNASSIGNED
We compiled a list of 714 genes associated with AD. From 5,833 drugs used for human diseases, we identified 1,044 drugs that could be potentially used to treat AD. Then, amyloid-β (Aβ) protein, the key molecule involved in the pathogenesis of AD was selected as the target to further screen drugs that may inhibit Aβ aggregation by molecular docking. We found that ergotamine and RAF-265 could bind stably with Aβ. In further analysis by molecular dynamics simulations, both drugs exhibited reasonable stability.
Conclusions UNASSIGNED
Our work indicated that ergotamine and RAF-265 may be potential candidates for treating AD.

Identifiants

pubmed: 39269834
pii: JAD240235
doi: 10.3233/JAD-240235
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Qiuchen Wang (Q)

School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.

Mengjie Fu (M)

School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.

Lihui Gao (L)

School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.

Xin Yuan (X)

School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.

Ju Wang (J)

School of Biomedical Engineering, Tianjin Medical University, Tianjin, China.

Classifications MeSH