Drug Repurposing for Newly Emerged Diseases via Network-based Inference on a Gene-disease-drug Network.
Mol Inform
; 41(9): e2200001, 2022 09.
Article
in English
| MEDLINE | ID: covidwho-1763266
ABSTRACT
Identification of disease-drug associations is an effective strategy for drug repurposing, especially in searching old drugs for newly emerged diseases like COVID-19. In this study, we put forward a network-based method named NEDNBI to predict disease-drug associations based on a gene-disease-drug tripartite network, which could be applied in drug repurposing. The novelty of our method lies in the fact that no negative data are required, and new disease could be added into the disease-drug network with gene as the bridge. The comprehensive evaluation results showed that the proposed method had good performance, with AUC value 0.948±0.009 for 10-fold cross validation. In a case study, 8 of the 20 predicted old drugs have been tested clinically for the treatment of COVID-19, which illustrated the usefulness of our method in drug repurposing. The source code and data of the method are available at https//github.com/Qli97/NEDNBI.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Drug Repositioning
/
COVID-19 Drug Treatment
Type of study:
Experimental Studies
/
Prognostic study
/
Randomized controlled trials
Limits:
Humans
Language:
English
Journal:
Mol Inform
Year:
2022
Document Type:
Article
Affiliation country:
Minf.202200001
Similar
MEDLINE
...
LILACS
LIS